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How to Address Data Management Challenges in IoT Using Fabrics

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August 7, 2023

How to Address Data Management Challenges in IoT Using Fabrics

Whenever we talk about data management, the whole conversation remains incomplete if we do not mention the most important aspect related to data management: the Internet of Things, IoT networks. Today, everything is connected, and all credits go to IoT networks. From smart towns to industrial sensors, our world is interconnected with smart devices, and the volume of data generated has reached unbelievable proportions. This is advantageous for our digital transformation initiatives but carries a parallel increase in vulnerability to data piracy, cyber attacks, and privacy infringements.

The amount of data generated is directly proportional to the higher stakes regarding safeguarding it. This raises the need for data protection measures in IoT ecosystems, which has now become a significant challenge for organizations. It has also necessitated robust data management strategies to guarantee IoT data’s integrity, security, and privacy.

However, enterprises are still making errors. They emphasize more on expanding IoT and are least interested in making the data streams safer and more authentic. More comprehensive IoT networks assure more users and faster streaming, yet they lack in terms of data protection.

Critical data management challenges in IoT

In the domain of IoT, significant data challenges emerge, including security risks, privacy concerns, data authenticity, and data proliferation. Security risks create a constant threat, as IoT devices are vulnerable to breaches, unauthorized access, and tampering, potentially resulting in data leaks and network attacks.

Safeguarding privacy is crucial due to the collection and transmission of personal data by IoT devices containing sensitive information like location, health data, and behavioral patterns.

Securing data integrity and authenticity is difficult in IoT environments, as changes often lead to erroneous decisions and compromise system reliability.

Besides this, the sheer volume of data created by IoT devices can overcome traditional management systems, making it necessary to have sufficient storage, processing, and analysis strategies in a timely and cost-effective way. As per the ‘State of IoT Spring 2023’ report released by IoT Analytics, the worldwide count of operational IoT endpoints rose 18% in 2022, reaching 14.3 billion connections.

How can data fabrics handle these challenges?

Data fabrics are essential in allowing scalable data management in IoT ecosystems. They provide valuable support in different aspects of IoT data management. They play a vital role in privacy protection by using data masking techniques that pseudonymize or anonymize sensitive information.

By substituting original values with masked or randomized data, the identity of individuals or devices remains safe, diminishing the threat of data breaches.

Data fabrics also allow access control, restricting access to authorized personnel or systems. Encryption also improves security by shielding transmitted or stored data from unauthorized access. Data fabrics offer an extra layer of security against attackers by integrating encryption with masking.

In addition, data fabrics support data minimization by reducing the amount of sensitive data stored or transmitted, using masked or aggregated data instead.

Data integration and aggregation: Data silos create a significant challenge in IoT, as they can cause data duplication, loss, or inaccessibility by different systems. Data fabrics can support breaking down data silos by offering a unified view of data across the IoT ecosystem. Data is created from different sources and in diverse formats; data fabrics can enable the integration of this data into a suitable view. This allows organizations to comprehend their IoT data landscape and make informed decisions. Data fabrics can collect and merge this data in real-time, offering a compressed and contextualized view of the IoT environment. This collected data can be used for real-time analytics, irregularity detection, and predictive modeling, allowing organizations to derive valuable insights and make proactive decisions.
Data processing and analytics: Data fabrics offer processing power, permitting IoT data to be analyzed and changed into actionable intelligence. By using distributed computing and parallel processing, data fabrics can handle IoT data’s high volume as well as velocity. This empowers organizations to conduct complex analytics on the gathered IoT data, like machine learning algorithms, extracting valuable patterns, trends, and correlations.
Data management and quality: Data fabrics offer a management layer guaranteeing data quality, consistency, and compliance. As we know, IoT data comes from different sources and devices, and it is necessary to ensure data integrity and reliability. Data fabrics can implement data management policies, perform data validation and assure data quality standards are fulfilled, thereby enhancing the reliability and trustworthiness of IoT data.
Scalability and flexibility: IoT establishment often includes multiple devices creating data at a high frequency. Data fabrics are designed to be scalable and flexible, enabling organizations to manage the high intensity of IoT data and acclimate future growth. They are seamlessly scaled horizontally, adding more resources as required and adapting to evolving IoT infrastructures and data requirements.

Not just this, data fabric tools also enable real-time data processing and help in decision-making. In IoT systems, real-time responsiveness is essential for upcoming maintenance, monitoring, and dynamic resource allocation applications. Data fabrics can process and analyze data in real-time, allowing organizations to take prompt actions based on IoT insights.

Some robust platforms for managing IoT data

For handling IoT data, many platforms offer robust capabilities. One such platform is K2View, a data integration and management solution that allows organizations to merge and manage their data from various sources. Their technique pivots around micro-data management, emphasizing granular test data management instead of replicating entire datasets. This strategy streamlines operations, decreases complexity, and minimizes the risk of data inconsistencies. Organizations can overcome data silos, improve data quality, and achieve valuable insights for informed decision-making using their scalable and flexible architecture.

For companies planning their AI move, IBM Pak is an available option. It is a pre-integrated, enterprise-grade data and AI platform that assists businesses in accelerating their journey to AI. It offers a unified view of data, streamlines data preparation and control, and allows rapid growth and deployment of AI models. It is also available on-premises or in the cloud.

There are other platforms like Talend, known for its data integration and transformation capabilities. Talend is a data integration platform that gathers, cleans, and converts data from IoT devices. It also offers a combination of connectors to other data sources, making it uncomplicated to build a data fabric. It also offers a set of data integration, quality, administration, application, and API integration capabilities. Their Fabric also supports organizations in getting trusted data promptly, improving operational efficacy, and reducing threats.

The realm of IoT- connecting everything

The Internet of Things (IoT) will become the most powerful domain in the coming years, and data fabrics will be the best solution to encounter and subdue data challenges. They empower businesses to break free from silos and gain a holistic view of their digital landscape. With the help of data fabric, real-time insights become the standard, promoting intelligent decision-making and growing businesses into new frontiers. With the adoption of this paradigm, data fabrics come out as beacons driving organizations to the vast intricacies of IoT data and unlocking endless opportunities.

Key Factors to Consider for Cellular Connectivity in IoT Product Design

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May 16, 2023

Key Factors to Consider for Cellular Connectivity in IoT Product Design

The Internet of Things, which had just a few applications before, is now part of almost every sector. Beginning from a smart bottle to a smart home, from smart buildings to smart towns, IoT has impacted every sector and will continue to do it. The integration of other technologies with IoT is also churning incredible results. Sectors, not part of it till now, are planning to embrace it with full potential.

IoT is diverse today, with a broad range of devices and applications connected with cellular connectivity solutions. By exploring various factors, product designers can possibly make the best connectivity options that suit the IoT solution.

This way, they are able to optimize the live operations of devices after they are deployed. Flexible connectivity is best for many installations, and to enhance this, the eSIM, wherever it is relevant, can support making the product more agile.

What aspects to keep in mind while considering cellular connectivity

Getting the proper cellular connectivity for IoT devices is crucial; otherwise, the whole purpose will be negotiated, leading to minimum output.

While designing for the IoT, one should consider the following aspects:

Device: The first thing to consider is the device because its deployment characteristics impact the choice of cellular connectivity. The aspects to consider are the lifespan of the device and the amount of power it requires to stay deployed. Mass deployments in remote areas, at the global level, or expansive locations require continuous power as they will likely stay in position for an extended time.
Data: The second thing to consider is data- what type and amount of data will the device need to exchange? The device may send only a tiny amount of data or need higher bandwidth to exchange videos. It is essential to consider how the device application may develop over time, for instance, from sending audio files to adding video. It does not matter what data or volume is being transferred; the connectivity should be secure because mass IoT deployments offer a large attack surface with constant risk. Therefore, it is vital to consider data value and multi-network resilience.
Distribution: If we talk about distribution, then we can simply say that it is a crucial consideration because network options and commercial arrangements will differ for national, regional, and international deployments. Having a single stock-keeping unit (SKU) for devices is always the best option, but that may not be feasible if devices targeted for different markets have different SIMs. In such cases, region-specific SIMs are to be implanted when devices reach their destinations for late-stage connectivity.
Coverage: This concerns the wireless technology which is used to connect devices. Low power wide area networks (LPWAN) (NB-IoT and LTE-M) are in favor, but their global coverage is quite in demand, and even at a national level, there are gaps. Make sure that your device has coverage and that there is no possibility you’ll need to deploy to countries with no LPWAN.

The phasing out of 2G and 3G

Many IoT applications were designed to connect over 2G and 3G. These networks are now being phased out; if we take the case of 3G, then switch-off has already occurred in many regions or is being listed in the to-do list in coming years. The main reason behind all this is that mobile network operators (MNOs) are trying to free up the spectrum for next-generation, cost-efficient, and better revenue-generating technologies. Most companies that use 3G for connecting IoT deployment will hold no place in their migration plans.

But in the case of 2G, everything is slightly different as this technology has been entrenched in large deployments of IoT devices and machine-to-machine (M2M), especially across Europe. Therefore, there is a high chance that 2G will not be disrupted in many countries until the end of the decade. While this might sound like a far-off thing, future planning is critical for devices deployed for many years.

There are 2G/3G connectivity options, each with its own features. These should be evaluated to assess their suitability for a new IoT device in design:

NB-IoT

This is the best solution for stationary IoT devices that share small amounts of non-real-time data, are solar or battery-powered, and are located where other technologies would not be able to get a signal. NB-IoT provides low hardware and operating cost, making long-term mass deployment viable. It is battery effective and can support devices that stay in the field for a long, like sensors with low and intermittent data. It also has full signal penetration, the most profound reach of any low LPWAN, and can cope with basements or underground car parking even if sensors are installed below street level.

LTE-M (Cat-M1): This provides the powerful throughput speed and bandwidth of any LPWAN technology to manage the over-the-air (OTA) updates of the future. It also sustains a wide range of IoT applications but is best for low-power devices that need higher speed or two-way data transfer, like those supporting SMS or voice services. It can be used for both mobiles as well as stationary devices, as it allows cell yo cell roaming. However, as already mentioned, some deployments would need help with either NB-IoT or LTE-M for the coverage causes. Today, neither LTW-M nor NB-IoT is available on 4G, and NB-IoT is currently not supporting eSIM.

In cases where these limitations make LPWAN useless, companies can consider the following:

LTE Cat-1 and Cat-1 BIS: LTE Cat-1 (Cat-1 BIS being the single antenna version) is a grown technology. Hardware costs and power consumption are pretty high in comparison with LTE-M and NB-IoT, but for some usage, the advantages will overshadow this issue. It receives global support as Cat-1 is a standard 4G technology, and traditional roaming agreements mean global network access is possible using a single SIM SKU. It is appropriate for mobile applications and goes well with eSIM also. Lower latency and increased bandwidth make Cat-1 a better option for 2G/3G and sustain a wide range of IoT applications. It fits nicely for low-power IoT devices that need high-speed and two-way data sharing or mobility. It also has a three-to-five-year battery life or application that uses rechargeable batteries.

eSIM adoption is already in process, and it is anticipated to be adopted within smartphones, enterprise IoT, and the wearables markets, with integrated iSIM technology following 2025.

As per research conducted by Counterpoint, it is estimated that shipments of eSIM-based devices will cover almost two billion units by the end of 2025 from 364 million in 2019. The report also shared that most eSIM-based devices will have a hardware chip-based eSIM solution until 2025.

eSIM for flexible connectivity

eSIM is one of the best technology, known for its flexibility, and also supports OTA provisioning of network operator credentials. This implies that the same SIM can be used in each device irrespective of where they go, as connectivity can be provisioned later. It delivers the single SKU essential for operational simplicity, particularly for large international IoT deployments. This makes manufacturing more uncomplicated and more streamlined, and connectivity uses local networks at local rates.

Additionally, eSIM allows in-life network operator changes without needing to swap out SIM cards physically. Through this, companies can leverage new commercial arrangements and attractive deals.

There are a few points to be taken care of while designing IoT devices with cellular connectivity. First, the device themselves, the data they will share, and the targeted areas where they will be used. These aspects will be crucial in determining the right cellular connectivity choice.

The second point to consider is that network technologies will not exist forever, as companies who have already done or are in the process of migration from 2G and 3G will understand. Hence the lifespan of the technology is another factor to be kept in mind.

The benefit of some technologies is their flexibility – the eSIM, wherever possible, brings agility to IoT deployments. In all, an IoT connectivity platform provider can help in determining optimal cellular connectivity for each IoT use case. To enjoy the leverages provided by the IoT system, one should never ignore the importance of cellular connectivity and whether the device is compatible with it or not.

By embracing an intelligent approach to connectivity and choosing an IoT connectivity partner that comprehends the potential eSIM brings but also understands the importance of managing different use cases in different countries in different ways, IoT organizations should ensure that they can provide optimized IoT connectivity continuously. Different countries follow different regulations; like Brazil does not allow permanent roaming for IoT devices, they can connect by using a local carrier only. Thus, the case of keeping connectivity streamlined and seamless just by having a single connectivity platform from one provider is attractive. The platform provider can handle all the changes and manage all the integration. Apart from this, deals of this type protect the customer organization from changes like geo-political changes that might compel an individual organization to reconsider its connectivity provision.

Which Network is Suitable for Your IoT Infrastructure: Wireless or Wired?

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April 26, 2023

Wireless or Wired Network: Which is Suitable for Your IoT Infrastructure?

Today, if we look around, we will get a clear view of how devices and smart products are dependent on data. From a refrigerator to a coffee cup, room ac to a smart home lock, street lights to a smart city, whatever is connected to the Internet of Things generates data. These devices are connected using either wired networks or wireless networks, depending on the need of the IoT system. Opting for the right and most-fitting network is crucial, as it determines the performance, safety, and future of the IoT facility. The option available comes with both benefits and constraints. But have you ever thought, what if you need a combination of both for your IoT facility? Is it possible to have such a network? Will it be able to connect multiple devices and adapt the future changes?

Let’s dive into the details of different networks present for the IoT facility.

Points to look into before picking the right network

Machinery in modern structures depends more on data rather than operators to function. This dependency on data has been triggered due to the introduction of the Internet of Things in the manufacturing industry. IoT-connected devices allow machine-to-machine communication in which devices in your facility can share information. IoT even allows transmission between devices and cloud computing infrastructures, which supports processing information.

The communication infrastructure of the installation delivers the data for IoT devices and M2M communication. It acts as a backbone of the facility’s communication. Therefore, businesses must think twice before choosing the network to connect their IoT installations. With the boost in the number of connected devices, the choice of the network has become essential for IoT-connected systems. The most popular classification between network types is wireless and wired networks. Both come with pros and cons, making it crucial to know which one will be perfect to complete the needs of the facilities.

While picking a network for your IoT facility, it is crucial to check different vital factors, including:

Cost: Cost is the primary thing to check before opting for a network; one should check the upfront and ongoing costs of each network, including installation, upgrades, and maintenance.
Security: Security is the utmost significant concern; it is crucial to know the standard of security offered and the potential for hacking and data breaches of the network.
Scalability: The capability of the network to stretch and adapt to changing and extending operations without negotiating with the quality.
Bandwidth: The amount of data your system should be able to handle; thus, choose a network that can match and complete the needs of your facility.
Latency: The latency needed to make the facility operations perform seamlessly.
Flexibility: The comfort and feasibility with which one can add or remove devices or make changes to the network.
Physical environment: The facility’s physical environment, such as any potential sources of signal interference and power sources, etc. Wired networks may be more appropriate for facilities with stable power sources, while wireless networks are best fit for remote or hard-to-reach locations.
Specifications: The specifications of the device that is connected to the network also play a crucial role. Some devices support only wired networks of specific protocols. Others might support wireless connection.

Besides the points and considerations mentioned above, the specific needs and constraints of the facility play an essential role in determining the right network for your IoT system.

Wired vs. wireless: Which one to opt?

Well, we can count on the factors mentioned above to produce a valid comparison between wired and wireless networks.

Cost: Wired networks are comparatively more costly in terms of installation as well as maintenance as they need the physical installation of cables. However, in the case of a wireless network, ‘n’ number of devices can be connected to a single wireless router. So, we can simply conclude that wireless networks are generally less pricey than wired networks.
Flexibility: As we know, wired networks depend on physical cables, making them less flexible compared to wireless networks. This can hinder in expansion or reconfiguration of your network, specifically when you need to add new devices or make changes to the existing physical layout of the facility. Hence, we can conclude that wireless networks are more adjustable than wired networks as they do not demand any physical cables.
Portability: Wireless networks can be employed in hard-to-reach areas, making them a good option for facilities that require mobile or readily available. Whereas wire networks do not have these advantages as it has no portability.
Scalability: Wired networks are less scalable as compared to wireless networks. This can create an obstacle in the process of expansion or reconfiguration of the network, especially when you add new devices or perform any changes to the physical look of your facility. Hence, wireless networks are more scalable in comparison to wired networks, as they can be extended and adapted with the expansion and transformation of the facility.
Security: In terms of security, wired networks are more secure and have less risk of signal interference or data loss. This makes them an excellent option for facilities that control sensitive data or demand high security. Wireless networks are more prone to security issues like hacking, security threats, signal interference, and data loss. This can place sensitive data or critical operations at risk.
Bandwidth: Wired networks are capable of managing large amounts of data, making them fit for facilities having high bandwidth needs. Wireless networks have limited bandwidth, which means that they may not be best for facilities with high data needs.
Latency: Wired networks face less latency in comparison to wireless networks, thus making them best for use cases that need low latency.
Stability: Wired networks are more stable compared to wireless networks as they are less exposed to signal interference or physical damage. This promises to ensure reliable and seamless connectivity for your devices.

Use cases of Wired and Wireless networks

Wired networks are used in facilities that demand large bandwidths, like data centers and manufacturing units. Wired networks are also best for critical systems that need constant, uninterrupted, and seamless connectivity, as they are less exposed to interference and outages in comparison to wireless networks.

On the other side, wireless networks are best for facilities with restricted space as they do not need physical cables and are easier to install and maintain. Wireless networks also fit facilities that need the skill to swiftly add or remove devices, as they provide excellent scalability and flexibility compared to wired networks.

For example, in the healthcare sector, a wired network may be the perfect option, as it provides stability along with security for critical systems.

But in a retail facility, a wireless network may be more appropriate as it offers greater flexibility and scalability in adding and removing devices. Walmart uses a wireless network solution for its stores to obtain real-time inventory tracking and boost efficiency.

A hybrid network is also an option

Apart from wired and wireless networks, IoT-connected devices can also opt for a hybrid network solution. Hybrid networks have the strength of wired and wireless networks and offer a balanced solution for IoT units.

For instance, a hybrid network could use a wired backbone for crucial systems and a wireless network for mobile devices, offering stability and security like a wired network with the flexibility and scalability of a wireless network.

Hybrid networks also provide many other advantages, like the ability to balance the costs and leverages of both wireless and wired networks. It also offers scalability, flexibility, and the ability to adapt to different device and application types.

However, hybrid networks are more complicated to implement and manage in comparison to single network solutions.

Whenever you opt for a hybrid network solution, make sure to consider the specific needs and constraints of your IoT system. Different factors like types of devices and applications, the physical environment, and access to power sources should be the utmost priority in the checklist. Besides this, it is necessary to ensure that the solution is scalable and can adapt to upcoming changes to the network.

Which one is the right network to choose?

Selecting the right network that can fulfill the needs of the IoT facility is the most critical decision, as it can affect the security, functionality, and efficiency of the devices.

This decision can be a challenging task as both offer pros and cons. On the one hand, wired networks offer stability and security; on the other hand, wireless networks provide flexibility and scalability. The selection between a wireless network, wired network, and hybrid network should be made based on the requirement and constraints of your IoT units. When deciding, one must also consider the cost, scalability, security, bandwidth, flexibility, and physical environment of the IoT system to ensure that it best suits the needs.

Consider investing some time to evaluate the options carefully; this will ensure that the IoT facility is well-connected and performs optimally, offering the data and insights required to drive business objectives.

How IoT Boosts the Micro Mobility Market

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December 8, 2022

How IoT Boosts the Micro Mobility Market?

The Internet of Things is no new thing in the tech market. Just look around, and you’ll find that most of the gadgets and comfort offering solutions are connected to IoT. One of the most popular and known solutions is your virtual assistant,” Alexa.” The way that device handles other internet-connected devices in our homes is incalculable. But limiting the character and usefulness to just these things would be unfair. IoT is also immensely used in logistics, manufacturing, industrial automation, and many others. Not just this, IoT is also being used in the micro-mobility sector.

Any idea about micro-mobility?

The word micro-mobility directs to lightweight transportation for individuals. It shields different transportation options that weigh less than 500kg (1200 lbs).

Some examples are electric scooters, bicycles, e-bikes, segways, electric skateboards, etc. Micro-mobility is very different from vehicles that are used for long distances. It focuses on short distances and generally for less than five miles. There are considerable advantages to the micro-mobility market, which is the reason behind the huge investment made by tech giants. In 2020 investment in the micro-mobility market was $800 million. This scenario rocketed after the lockdown restrictions were removed. The micro-mobility brands drew around $2.9 billion in 2021.

Advantages of the Micro-mobility Market:

Let us know three specific benefits of the micro-mobility market that support these high investments:

1: Convenience

One of the most popular and justified benefits is convenience. Transportation options can help customers reach their destination early and with comfort.

2: No Parking Issues:

Parking is one of the major issues in big cities, but micro-mobility can solve this problem. You will never again face parking issues by using micro-mobility transportation choices like segways and hoverboards.

3: Cost-Effective:

As micro-mobility involves ride-sharing, it will automatically become cost-effective; you can rent without requiring any license for hoverboards or e-bikes.

Challenges Faced by the Micro Mobility Sector

The idea of micro-mobility appears appealing, but some challenges hinder the growth of businesses. However, there is zero to be upset about as long as IoT exists, as it has the potential to advance the micro-mobility market.

Data Sharing:

Suppose your own a firm that has 100 ebikes throughout the city. People take your ebikes but pay less attention to the charging levels, and why would they? They are your service bikes, and it’s your responsibility to take care of them. Well, not just this, there are many other issues like ending the ride midway, navigation issues, leaving the vehicle anywhere, and overriding the ebike that can cause damage and revenue loss.

Therefore, there is a need for a solution to collect all the necessary data about the vehicle from time to time. With IoT-connected devices like highly sensitive sensors, one can quickly get all the data related to the vehicle for analysis and make informative decisions. Moreover, adding IoT sensors will also make it manageable for you to transfer data with the traffic authorities to watch vehicle activity in a good way.

Riding Behavior:

It is pretty noticeable to see people riding aggressively on the road. This can be inspired because of different reasons like road rage or time-saving. However, no reason justifies the purpose as it can distract or put other’s life at risk. With IoT sensors installed on the vehicles, businesses can check the vehicle status and warn the rider by sending messages.

For instance, if a person is riding at high speed or cutting the lane often, sensors can record the data and share it with the related authorities for further action. This can protect vehicles from damage and save companies from getting banned due to abnormal riding behavior.

Safety:

Whether a car or a scooter, safety remains the top priority for micro-mobility service provider companies. It is essential to integrate features that protect the riders. These added features are not just limited to safety but also allow businesses to meet government requirements to secure their business.

Theft and Vandalism:

A micro-mobility company’s worst loss is when a vehicle is damaged or lost. Therefore, it is necessary to install proper security measures to prevent this from happening, and yes, IoT can help with this. By implanting a few IoT sensors, companies can stop stealing ebikes. Additionally, these sensors can also be connected to other systems to initiate warning messages.

If it is a genuine user, they can use their phone to get an OTP and use the ebike. Further, the vehicle can have environment-mapping sensors to prevent vandalism.

Scaling Service:

IoT can help in business scaling, but the critical challenge with IoT is that one needs to modify the complete system to upscale instead of a single one. The most feasible option is to get the most suitable IoT service providers. A single service provider will promise smooth and seamless scaling as the operator would have knowledge of your business operations.

Compliance:

Compliance with government standards and norms can hinder growth as they may change and be difficult to follow. However, if state-of-the-art IoT solutions back you, they can become more accessible. IoT sensors can be employed to keep riders stay within speed limits. It can guarantee that vehicle is parked at the right spot. In fact, smart sensors can also guide the riders to the nearest charging station. These criteria also guarantee that riders do the right thing and that government norms are obeyed.

IoT and Micro-mobility

IoT can support the upheaving micro-mobility market, but the only condition is that this will demand colossal investment. Once an investment is made, all other systems are managed, and only timely maintenance and upgrade is left. Investment in IoT for the micro-mobility sector promises a better future and benefits, and various tech giants like Uber and many others are forwarding toward it. This shows that micro-mobility holds a great scope in the coming years. It not just brings transportation at ease but also promises its contribution towards the environment by reducing the dependency on crude oils. The integration of micro-mobility with IoT makes it safe and futuristic.

How Artificial Intelligence in the App Industry is Changing the Future

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November 3, 2022

How Artificial Intelligence in the App Industry is Changing the Future

“Artificial Intelligence is no more in fiction stories now. Today in our daily life, we can observe AI performing different tasks.“

Even if it is a customer or business organization, machines are vigorously improving the intelligence of humans. The mobile app sector is growing day by day. After the covid hit the world, it has become the basic need of many companies. For customers, it has become a way to reach the maximum number of things through the mobile application. With the involvement of AI, it is changing at an incredible pace, and the users get the best use of the app to meet their basic daily needs.

What is Artificial Intelligence?

It is a system capable of imitating intelligence and behavior to work and act like humans. It is possible because of some of the algorithms. It provides a virtual assistant without any human intervention. AI delivers predictive messaging, learning and planning capabilities, and voice recognition that will assist in understanding the language. It holds impressive skills in solving problems. It just does not work for business organizations but also magically works for customers. It fetches the best solution to help your business flourish and build a strong customer relationship.

Benefits of AI

It provides the best output of investment where the marketers will receive essential feedback from the users. Digital marketing for all kinds of businesses guarantees that return is always two-way. Both customers and organizations should get the return they expect to survive in the competitive tech world.
AI also assists in developing customer relationships. It is challenging for an organization to personally connect with each customer’s problem. In such cases, AI works as a savior. Whenever the user reaches customer service on the app, AI offers incredible help and gives the most-suited solutions to the users. Therefore, creating a good relationship with the customer.
AI also enables the company to make a fast decisions on any strategies. It assures that the company can access real-time situations; AI provides qualitative customer and business decisions. It is the most convenient way to connect with the process and gain success in the field.
Market measurement plays a crucial role in the business. AI offers the best market measurement where the company is aware of the risks and benefits of an issue.

Here are the following ways through which AI is supporting the mobile app industry:

Internet of Things (IoT):

Today, many devices are connected to the internet. If not mobile, the internet connects with a fitness tracker, kitchen appliances, watch, TV, etc. The connected device collects user activity data and provides powerful insight. Both AI and IoT work together so that customers get the most enhanced experience. With the support of digital assistance, the developer is able to develop an app that will easily connect to the TV.

AI is connected with sensors in broad options and offers a location-based experience. AI is most appreciated in app development and is helpful in building the best app.

Automation development:

Development of the app demands excellent skills. In the process, many tasks are to be completed, which eats up time many times. However, by using AI, the development team can easily save time as well as money that can be used to automate the process. Not just this, AI can provide consistency and eliminates errors. AI can also help in skipping the repetitive tasks and mistakes caused by it.

AI chatbots:

When you visit any website, you’ll see a chatbot below the website. If you click on the chatbot and fill in your details, AI will identify your need and pattern and reply accordingly. If your problem has a solution, AI will immediately solve it and give sales support and customer service.

Understand user:

Selecting the clues from the users, AI comprehends what the users need and assure that they get the same thing. It analyzes the activities and behavior of the user and provides the best suggestions. Additionally, they can understand the user’s behavioral patterns and apprehend the users’ needs.

Personalization service:

We all know that every customer’s need is different from each other. Therefore, customization is the best way to offer customer satisfaction and will boost sales. The modern AI service will ease the work of developers and offer the best-customized services. AI detects the customer’s pattern, taste, or preference. It suggests the same interest and preferences so that customers get engaged and shop from the options.

Mobile App Industries that use AI to change the future

Healthcare App:

Now, healthcare services are just a dial away. You can get the best healthcare services at home and receive the reports in your mail. With the inclusion of AI in services, a patient’s medical details are now collected, stored, and managed efficiently.

Automotive App:

In the automotive sector, all the brands are embracing the latest vehicles where Artificial intelligence enhances the driving experience. While driving, one can use AI features for navigation and listening to music. Driverless cars are next-level features offered by AI.

Finance App:

In the banking sector, AI is helping customers to save money by educating them on where to invest. It assists them so that they can track their expenses and manages everything on points. It assures that finance sectors can help customers in solving their problems while sitting in their homes.

Law App:

Sometimes it takes work for attorneys to answer all the questions in person. In that case, AI can help by answering all the legal questions to clients so that they get answers to all their doubts.

Conclusion:

Though Artificial intelligence has its challenges, it still never fails to improve the app industry. Today, many app owners in various sectors are using this technology to stay updated with the trend and customers as well. AI ensures they can create a good relationship with the customers by recognizing their behavioral patterns in shopping or anything else. Therefore we can conclude that Ai is more than a technology. It is a blessing for app owners to develop a good relationship with customers.

Which solution is best for your Connected Device- Edge or Cloud Computing_

admin

September 5, 2022

Which Solution is Best for Your Connected Device – Edge or Cloud Computing?

If you have adopted IoT and are developing an IoT-connected device, you may wish to do some valuable computation to resolve the important issues that have been hindering growth. You might be desiring to install sensors in remote locations, create a device that can do data analytics to watch a renewable energy source, or develop health-related devices that can detect the early signs of diseases.

While creating the IoT-enabled device or IoT solution, at some point, you might get into a dilemma where you have to choose between edge or cloud computation. But what would be best for your device? Where should your device do the valuable computations in the cloud or at the edge?

Selecting between computing on edge or cloud can be an impacting decision, like it can influence a device’s efficiency or cost. Therefore, everyone does great research and thinks twice to avoid the cost of making the wrong decision and then the money spent correcting it.

What is Cloud Computing?

Cloud- It is a collection of servers accessed over the internet. Some renowned cloud providers are Microsoft Azure, Amazon Web Services, and Google Cloud.

These servers offer on-demand computing resources for data processing and storage purposes. You can easily say that cloud is a centralized platform for storing your files and programs, and you can easily connect any device to the cloud to access the data. Some of the cloud-based services are Dropbox or Google Drive etc.

Cloud computing is the process of doing computation in the cloud. These computations include data analysis and visualization, machine learning, and computer vision.

What is Edge Computing?

Edge is described as the “edge” of the network that includes devices at entry or exit points of the cloud, but it is not a part of the cloud. For instance, a server in a data center is part of the cloud; however, smartphones and routers that connect to that server are part of the edge.

Edge computing can be defined as the process of performing computations on edge. In this, the processing is completed closer or at the location where data is collected or acted.

One example of an edge computing process is object detection attached to an autonomous vehicle. The vehicle processes the data from its sensors and utilizes the result to avoid obstacles. In this process, the data is processed locally rather than sent to the cloud.

What are the points to be considered?

Before opting between edge and cloud computing, a few key questions must be considered.

Quality of Your Device’s Network

Conducting computation on the cloud can be beneficial if you have high bandwidth, low latency, and a sturdy connection to the internet, as you’ll have to send your data back and forth between cloud servers and your devices. If you have to use your device, for example, in an office or home with a steady internet connection, this back and forth can be done seamlessly. In most cases, if computation is conducted on edge, it won’t be affected by the bad or lost internet connection in a distant place. The processing can continue as it is not performed in the cloud. You would never want your vehicle’s objection detection to be failed while driving on the road. It is one of the reasons why autonomous vehicles perform computations like object detection on edge.

How Swift and How Often Does Your Data Need to be Processed?

Edge computing can be best suited in cases where customers demand response times from devices prompt than waiting for it in a decent network connection, such as monitoring components of the device.

The latency of the travel time between the cloud and the device can be minimized or eliminated. It means data can be processed immediately. It implies that if data processing is quick, one can achieve real-time responses from the devices. Cloud computation is also useful when device use is unsteady. For example, smart home devices running computation in the cloud allows sharing of the same computing resources between multiple customers. This decrease costs by restraining the need to provide the device with upgraded hardware to run the data processing.

What Part of Your Data is Crucial to You?

Computing on edge is helpful if you are only concerned about the result of your data after it has been processed. One can only send only important things for long-term storage in the cloud, which may cut down the expense of data storage and processing in the cloud. Suppose you are developing a traffic surveillance device that needs to inform about the congestion situation on the road. You could pre-process the videos on edge- instead of running hours of raw video in the cloud-one can send images or clips of the traffic only when it is present.

Do you know Your Devices’ Power and Size Limitations?

If you think your device will be limited in size and power, provided it has a strong network connection, sending the computing work to be done on the cloud will permit your device to remain small and low-power. For example, Amazon Alexa and Google Home capture the audio and send it to the cloud for processing, letting complex computations run on the audio as it can not run on the small computers inside the device themselves.

Data Processing Model Your Intellectual Property?

If you are creating a device for costumer and the methods you are adopting to process data are part of Intellectual Property, you must rethink the plan to protect it. Placing your IP on your device without a proper security plan can make your device vulnerable to hacks. If you are unaware of resources to secure your IP on edge, it is best to opt for the cloud, which already has security measures.

Final Reasons for Choosing Between Edge and Cloud Computing

Hence, we can conclude that one must consider a few things when choosing between computing on edge or the cloud. In complex issues, you might find the combination of both very beneficial by leaving some parts of processing on the cloud and rest on the edge.

How will IoT Build a Bright World with Connected Devices

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July 11, 2022

How will IoT Build a Bright World with Connected Devices?

Internet of Things is now no new word for the tech world. Studies show that the number of connected devices will reach more than 75 billion by 2025, implying that there will be possibly nine connected devices for every human on earth.

The pace at which IoT technology is striking every area of our lives is impressive, but how it has transformed our day-to-day work is beyond imagination.

But what is IoT?

In simple words, it is the practice of connecting different physical assets through the internet, providing control and measurement access from the remote area while saving users money and time. Today one can set the temperature of the air conditioner while on the way home, brew coffee and efficiently manage the use of lights in the home. Products like Amazon’s Alexa and Apple’s Siri can interact and provide information as required.

Let us know how various industries are embracing the presence of the Internet of Things and the impact of this latest technology.

IoT in the manufacturing sector:

The impact of Industrial IoT technology is already visible in the output of the manufacturing industry, especially in measuring energy and asset efficiency throughout the production line.

IoT technology has provided an effective way to connect and modernize legacy assets. Using connective sensors, businesses can accumulate critical production data and use cloud software to turn this data into useful insights to know about the efficiency of their manufacturing process. But what kind of assets? It can be anything used within the manufacturing process, from its HVAC or CNC machines to products like refrigerators or lighting rings, etc.

IoT can assist by providing a clearer picture of the working of assets individually and collectively, chartering better ways for monitoring, automation, and predictive maintenance. For instance, Industrial IoT in action has enabled us to gain insight into energy consumption and the health condition of the asset. This technology even allows us to schedule maintenance by informing us about the future condition of the asset.

Employing and integrating IoT in the existing process reduces costly downtime, improves assets, and reduces energy costs.

IoT in the retail sector:

Retail sectors are already using IoT in different innovative ways. One of the key areas is tracking energy consumption not at one store but all the stores present in the entire region or at the national level.

The IoT system can also be used to know which stores are using high energy in lighting or heating; in-store sensors allow us to track energy usage at a more granular level.

Other than this, IoT is also used to optimize store experiences. It is now possible to know the interest area of the shoppers, where they are spending most of the time. This helps retailers improve their stores’ layout to reduce congestion, increase stay time and boost sales. We can say that IoT technology and its different uses are building the ‘high streets of the future.

IoT in the construction sector:

Internet of Things is also contributing to making the construction sector smarter. Smart buildings are one of the most loved concepts possible by IoT. Using IoT and integrated sensors to know the air quality of the site or the surrounding area, such as parks and schools, is one of the key usages.

IoT in construction areas allows construction managers to accurately assess the real-time effect of their work on air quality. IoT in construction also ensures the safety of construction workers and nearby people.

IoT in the agriculture Sector:

The increasing population shows that we will need more food production in the coming year. UN has also estimated that we will need to produce 70% more food to meet the global demand by 2050. Internet of Things will help this sector overcome the looming food shortage challenge by reducing food wastage and increasing yield.

Supervising and tracking workers, machine efficiency, crop and livestock health, and predicting weather are some of the ways through which IoT promises to boost productivity with minimum wastage. Employment of agriculture drones and smart agriculture sensors are already helping agriculture workers by providing real-time production data. Besides this, sensors to track important atmospheric aspects like light, humidity, temperature, air quality, and soil aspects like soil moisture, nutrition, etc., contribute to better yield. This has automated the tasks which involved manual and human interference. Thus, saving labor costs and time as well.

Another way through which IoT is helping agriculture farmers is by providing predictive analytics through better quality data. Using data, farmers can estimate the yield and make better storage plans to keep the produce after harvesting.

IoT in smart cities:

Well, IoT in urban areas has been very influential. People are enjoying the leverages provided by IoT like smart houses, smart street lights, or smart bottles. IoT has occupied an important place in the planning and management of cities. Many countries are using IoT for waste management, traffic control, and public transport systems.

Using IoT, it is now possible to know the number of people in transit at a particular time and opt for a better route to avoid congestion. In cities where flooding is a serious concern, IoT can be used to track the real-time water level in the river. The flood defense system starts when the water level increases and helps mitigate the risk.

We’re on the way to a smart connected world:

IoT has successfully infiltered in major sectors contributing to the economy’s growth. Today, if we look around, we’ll observe that everything is getting smart and automated. All thanks go to IoT for making life more hassle-free and productive. However, some areas are still untouched by the magic of IoT, but it is predicted that it will be covered soon in the coming years. It is estimated that global expenditure on IoT will be around $1,100 billion (€1060.02 billion) in 2023, almost double 2018 $646 billion (€622.52 billion).

This shows that IoT will continue to reform the industries making them more profit-oriented without compromising quality. Hence, we can conclude that high-quality data can help make anything prompt, cheap, and more efficient with less waste.

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June 7, 2022

Role of IoT in Electric Vehicle Monitoring & Management

Today we are witnessing the temperature rise, and one of the major reasons behind this is air pollution. The emission of global house gases is worsening the situation, and its continuity might leave the earth unfit for humans in the coming years.

Vehicles are one of the major contributors to air pollution; therefore, it has become a major issue to look after. Today, people and the government are looking for ways to handle this issue. One of the best ways to control air pollution is by replacing fuel-based vehicles with electronic vehicles. Electric vehicles (EVs) are a new and environment-friendly innovation in this direction.

Electronic vehicles are hi-tech machines that collect an immense amount of data to deliver optimum performance. The performance parameters incorporate monitoring speed, mileage, acceleration, battery management, fault alert, charging, and predictive maintenance systems. Therefore IoT plays a crucial role in the monitoring of electric vehicles.

What is the role of IoT in Electric Vehicle Management?

Let’s know each aspect of an IoT integrated Electric vehicle management system and how they help obtain the optimal performance of electric vehicles.

Battery Management System:

The primary function of the Battery Management System is to watch and control the battery’s functioning. This implies monitoring the charging and discharging cycle to ensure battery health and minimize the risk of battery damage by assuring that optimized energy is provided to run the vehicle.

The monitoring circuit in Battery Management System (BMS) monitors the key parameters of the battery, that is, current, voltage, and temperature during charging and discharging conditions. It assesses parameters like power, State of Health (SoH), and State of Charge (SoC) and assures good health based on the calculation. Internet of Things exhibits a vital role in monitoring and controlling as it allows remote data logging facility for battery parameters, conditions, etc. Most EV manufacturers use high-quality Li-ion battery packs as they have a longer life and exceptionally high energy density.

However, there are some drawbacks as well. In situations when battery malfunction happens, the onboard sensor data acquired using IoT can aid in managing the issues. Then, these can operate through AI-based models for performance estimation. Tests can be executed on some Li-ions to evaluate the patterns of partial and full charging and discharging. Models are marked using the data gathered from each step and are integrated with Artificial Intelligence before deploying on a server. The EV sends important sensor data to the server, delivering insights on the next course of action and performance. We can conclude that the server checks the condition of the Electronic Vehicle.

Safety and Smart Driving:

The adoption of Iot also allows real-time monitoring of the vehicles and their parts. It helps in preventive maintenance provided by the technology, which is found to be more reliable by the users. IoT devices attached to EVs can offer the following features to the users.

It can measure the exact parameters of the driver like speed, acceleration, and many other things to offer real-time tips to ensure optimal performance.
It can prevent theft by real-time tracking, geo-fencing, and immobilization. This ensures better safety and security to diminish the dependence on insurance.
It also checks the performance data of the vehicle, based on which EV and battery OEMs can enhance thee products. Here parameters are the range of each charge, use of a vehicle, performance difference based on geography, age, weather conditions, and adjustment in range for each charge over a certain period.

Fault Alert and Preventive Maintenance System:

Electronic vehicles also face technical glitches as other machines do. IoT-enabled fault alert systems can help alert vehicle drivers about the EV faults, providing them time to act and address them before it’s too late. Though EVs are well designed to prohibit errors, sometimes parts might fail or stop.

To anticipate this, AI algorithms and remote IoT data play a vital role. They help alert the EV users and provide them time to resolve the issues before they actually happen. This enhances customer experience as they can rely on it for optimal performance. In addition, it is necessary to know the overall temperature and moisture conditions in various geographies, and keeping a check on remote performance is essential. These factors will help resolve the issue promptly and promises comfort and security to the user.

Telematics Data:

By using IoT-based telematics technology, data is gathered when linked to the vehicle sensors, shown through widgets, instant notifications, and produce automatic reports.

Let’s look at the useful factors of employing telematics for monitoring distant electric vehicles.

Battery Usage Data: Electric vehicles with telematics allow users to track real-time battery usage data. It lets users check important parameters like current, voltage, and temperature to skip battery breakdowns. Battery usage of EVs can be recorded and shared to a remote server that empowers to customize the battery configuration and enhance the best charging practices.
Charging Report: The addition of telematics in electric vehicles allows to yield reports on the vehicles’ entire charging sessions, i.e., the entire lifespan. The charging report shows the time duration, location of the charger station, and percentage of charge received by the vehicles.
Nearby Charging Stations Alert: Electric vehicle users encounter challenges like knowing state-of-charge(SOC) to schedule when and where to charge. Electric vehicles keep a tap on solutions with telematics and alert the user concerning the vehicles’ low battery level and the informs about the available nearby charging station.
Driver Behavior Data: Electric vehicle remote monitoring system with telematics ensures safety by monitoring and analyzing the electric vehicle performance data and also checks the behavioral data of the driver. Telematic provides quick feedback on driver’s behavior changes to fleet managers/owners through IoT enabled smartphone app. This ensures safety and improvement for better output.

Challenges of IoT in Electric Vehicle Management

Let us know some possible challenges of IoT for monitoring electric vehicles.

Cybersecurity:

The generation of the high amount of data and its transit over a network makes this data vulnerable to cyber-attacks and data leakage. Therefore, it is essential to strengthening the IoT networks used in the EV system to ensure no data leakage.

High Cost:

IoT systems in EVs are expensive. They are highly advanced and have high installation and operating costs. Thus, this technology requires more R&D, and the future might provide better and more cost-friendly IoT solutions.

Weighing the Benefits & Challenges:

We can conclude that IoT plays a crucial role in monitoring electric vehicles. The performance parameters enclose monitoring speed, mileage, acceleration, battery management, fault alert, charging, and predictive maintenance systems.

Overall, IoT holds an important place in the success of electric vehicles. However, challenges like cybersecurity should be considered seriously. EVs are innovative steps toward the environment, and their success will promise a better and green future.

How is Data Science for IoT changing business outlook

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May 26, 2022

How is Data Science for IoT Changing Business Outlook?

The Internet of Things has been noticed as a shape-changing technology that has changed the shape and working process of everything it has touched, either businesses or our daily lives. It has changed the outlook of every individual living a mediocre life into a smart device-connected life.

IoT connected devices produce tremendous amounts of data wirelessly over the network without any human interference, which is proved to be best for organizations trying to offer the best services to their clients. The only challenge is that IoT generates immense data for traditional data science.

Data Science and How It Applies to IoT

We can simply define data science as a study of processes that assists in extracting value from data. In the IoT system, data is referred to information produced by sensors, devices, applications, and other smart gadgets. Meanwhile, value means predicting future trends and outcomes based on the data.

For instance, suppose you are using a fitness tracker that calculates the number of daily steps. Using this information, data science can predict that:

Amount of calories burnt by you
How many kgs do you lose
When is the possible best time for your workout

This is a simple example of how data science works. Internet of Things is different as it produces high-volume data.

As per the reports, the amount of data to be produced by IoT by 2025 is around 73.1 zettabytes. This will cause trouble for standard data science as it cannot handle it, so it will have to update. Thus, IoT will help data science to go to the next level.

What are the Differences Between Traditional and Data Science for IoT?

There are only a few differences between traditional and IoT-based data science, so here we will check a few critical distinctions.

Data Science for IoT Is Dynamic:

The traditional version of data science is static as it is primarily based on historical information. For example, a company collects data from its clients about their choices and needs. The historical data becomes a base for predictive models that assist the company in understanding its future customers.

On the other hand, IoT changes the dynamic of data analysis as it is all about real-time sensor readings from smart devices. The gathered information permits data science consultants to create highly precise evaluations instantly.

In this case, customer data changes and updates- a feature that is not available in traditional data science. Data science for IoT allows continuous learning, changes with time, and improves operational processes simultaneously.

IoT Drives Larger Data Volumes:

Data science is developing with IoT because of its immense data processing. Here we are not discussing megabytes or gigabytes of data but data science for IoT deals with a massive amount of data that often reach zettabytes.

Better Predictive Analytics Method:

Data science for the Internet of Things is dynamic and wider than the traditional one. Additionally, it also makes a better predictive analytics method.

Thus, data science assists businesses in a great way; using it, businesses can develop better solutions that can diminish operational costs and acquire business growth.

IoT can improve this further through its real-time capabilities. IoT helps make decisions more accurate, assisting companies in identifying new opportunities and improving sales and customer experience while optimizing performance.

The Challenges faced by IoT Data Science:

We all know that data science for IoT holds vast potential, but it comes with challenges. Four major risks have to be overcome before it becomes mainstream.

Data Management and Security:

IoT produces a tremendous amount of data, which also implies that there are high chances of hacking or leaking private information. For example, Suppose hackers hijack the connection between the fitness tracker and doctor’s office app; they can easily access sensitive health records. Thus, it is pretty clear that privacy problems are the major issues with IoT data science.

For instance, many companies often face backlashes for releasing customers’ sensitive information without their consent.

Scaling Problems:

IoT data science is also important, but users often struggle to scale it up to fulfill their demands. When an organization plans to integrate an IoT system or add new sensors to its existing software solutions, it faces some issues and challenges.

Therefore, it is important to prepare for scaling projects in advance. Businesses must set up everything from software to personnel to scale data science processes successfully.

Data Analytics Skills:

Data science for IoT is extensively helpful, but classical data science consultant holds good dominance in the market as IoT analytics is still not very much embraced.

However, this could change soon as more companies adopt IoT technology. IoT scientists will have to add new skills and understand the oddities of the deployment process. For this purpose, they’ll have to learn about the following:

Edge Computing: It is defined as the practice of processing data close to the source to improve performance and reduce network congestion.
Computer-Aided Design: It is essential to know the logic behind the physical design of a smart device.
IoT Computing Frameworks: Data scientists must also employ open-source learning tools to grasp IoT hardware.

Operating Costs:

Another major problem with data science for IoT is the huge cost required to introduce new technology. This is the case for most companies willing to join this latest technology on a larger scale but is restricted by budget.

The Bottom Line:

We can conclude that data science for IoT brings a major upgrade to traditional data analytics. It requires efforts and dedication to make data science more robust, powerful, and accurate. IoT can make it possible through data generation abilities. The interconnected devices over the internet constantly communicate to offer businesses a huge amount of user-related data. This allows data scientists to draw relevant conclusions from their databases.

However, the process of deploying data science for IoT is not an easy task, but the benefits it provides negate every challenge. So, we can expect data science for IoT to be a part of the future at a great scale.

How is IoT Helping The Procurement Team in Improving Productivity

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May 13, 2022

How is IoT Helping The Procurement Team in Improving Productivity?

Today, almost every device is connected; whether it is your smartwatch, air conditioner, or television, we can say it’s a world where devices are more connected than people. No, doubt these connected gadgets present around us make our lives easier by working systematically. This is possible because of the most popular concept known as the Internet of Things, which can also influence the procurement team.

IoT, a.k.a Internet of Things, can be defined as a network of interconnected computing devices, either mechanical or digital machines. This technology allows transferring data without human-to-human interaction or human-to-computer interaction. Communication is possible using networks and cloud-based systems.

An IoT ecosystem includes web-enabled smart devices that collect, send and work on data collected from their surroundings utilizing embedded systems such as CPUs, sensors, and communication hardware.

IoT devices can exchange sensor data stored in the cloud for analysis purposes or examined locally by interlinking to an IoT gateway or other edge devices.

Besides this, these gadgets can connect with other related devices and respond according to the information they receive from one another. Even individuals can operate the devices for the beginning setup, give instructions, or recover data; the device can perform most of the tasks without human interference.

The Role of IoT in Procurement

Procurement is an important part of the business. It demands the implementation of new technologies to boost productivity, enhance customer service and save costs. As of now, the procurement process is also embracing automation; IoT in this process is one of the most exclusive things happening in the era of digital transformation.

The inclusion of the Internet of Things will provide greater spending visibility and understanding of the supply and equipment used for the procurement process. So, with a proper understanding of what is being used and the requirement specified, the procurement team will have access to optimize catalogs and manage expenditure. Forecasting demands more closely using analytics can significantly improve budget and contract management. This also helps in improving budget and contract management. Despite this, the data generated through IoT sensors and other devices can assist in making informed decisions.

Let’s know how IoT works in procurement.

Traceability of Materials:

A study done by a McKinsey Global Institute shows that by the end of 2025, the Internet of Things’ possible contributions to inventory management, logistics, and supply chain management would reach 560 billion to $850 billion per year. This shows the possible IoT-oriented future awaiting us. Most of the time, IoT contributes to these sections by tracking. IoT sensors can help in making inventory management systems more effective.

For instance, RFID tags connected with IoT devices can track physical inventories and eliminates the need to scan barcodes or labels. In fact, businesses with vast inventory can track the days before items expire using interlinked IoT devices, saving the business from huge losses. IoT also prevents product theft by enabling businesses to know the location of their products.

With the use of machine learning, procurement teams can manage products per demand.

Supply Chain Visibility:

In this process, the procurement team can also potentially use IoT technology. Supply chain visibility, items are documented as transported from the manufacturer to the customer. An IoT-enabled system can read data from various devices like smart tags and sensory data like surrounding temperature and humidity, vehicle speed, and geolocation and accordingly follow the supply chain when connected to it.

The adoption of IoT devices to track inventory and route planning provides the details about where and when items are delayed in transportation. This allows emergency planning and identification of other options to accelerate the supply chain.

Stock Management:

Along with smart shelves and storage bins that inform about the stock levels in real-time and how long the product has been on the shelf, IoT also assists in detecting the pattern of consumption.

For instance, if a product named X is on shelf A and has been the quickest utilized item, IoT sensors will monitor the usage rate and suggest its economic order quantity (EOQ).

This clears how essential procuring an item is, which products are needed, and what amount. Procuring the right inventory quantity reduces costs by lowering waste and the menace of shortage.

Monitor and Alert Maintenance:

The sudden breakdown of equipment in a production unit is the most horrifying dream as it disrupts the business. If the condition of the equipment is not known, things become more difficult and result into process disturbance, indefinite downtime, and even business loss. Regular monitoring of the equipment’s condition through IoT sensors permits the team to watch indicators like vibration, oil, temperature, and performance.

When these indicators go out of range, the sensor alerts the team via computers.

In fact, smart sensors also alert when a machine’s working pattern changes or is about to fail. So this allows teams to schedule the maintenance, decrease the chances of sudden machine failure, and ensure seamless productivity.

Better Decision Making With Predictive Data Analytics:

Procurement teams can predict the future using predictive data analytics and spend analytics. These predictions assist in making critical decisions for designing and executing business techniques. Continous flow and accumulation of data with IoT devices also help create more robust and relevant historical data.

Infact, joining IoT data with additional data coming from other sources can boost business growth.

For example, knowing what quantity of a product is needed can help send accurate requisitions for approvals and create error-free purchase orders.

For example, having information on what quantity of a product is being used can help in sending accurate requisitions for approvals and generating error-free purchase orders. This results in an efficient and effective purchase management system. Data collected by IoT can also be used for onboarding suppliers with supplier management solutions to get new products based on previous performance metrics and set criteria.

IoT Procurement Takeaway:

The Internet of Things has become a sensation and is impacting almost every industry. So, it will be smart to invest in this technology and unheave the existing business model.

The procurement team requires a comprehensive IoT framework consisting of machine learning, artificial intelligence, and embedded technologies. These technologies, all together, can bring holistic change and offer maximum benefit.

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