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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.

How can IoT Sensors Improve Productivity in Manufacturing

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April 18, 2022

How can IoT Sensors Improve Productivity in Manufacturing?

Internet of Things has been reaching out to almost every sector, and as a result, it is expected that the global IIoT market will reach $103.38 billion by 2026. Today IoT devices are more affordable, and many manufacturers invest in smart factory technology. One of the significant parts of smart factory technology is IoT sensors. It is essential to gather the necessary information and send data to the cloud for analysis in manufacturing. Businesses analyze data collected from the sensors to produce the most fitting solution to enhance productivity, avoid unplanned downtime, and cut manufacturing expenses.

IoT Sensors

In the Industrial Internet of Things, sensors are able to detect different types of external information and change it into data or signals that humans and machines can comprehend. Data is stored in a database which is managed either on the cloud or within the building for processing and analysis.

IoT sensors employ different types of technology like optics, infrared and thermal to catch the required information. Sensors can also collect one or many kinds of data. Sensors include measuring distance, levels, pressure, environment changes, or anomalies in production line batches.

Types of IoT Sensors

Vision Sensors:

Images are caught by a camera and processed using software to know parts’ presence, orientation, and accuracy. Adoption of vision sensors ensures product quality and consistency throughout batches. It is used chiefly on automotive, food and beverage, and general manufacturing production lines.

Proximity Sensors:

This sensor is used to calculate the distance between two objects. It is used primarily in manufacturing, where machines must know distances between products or measurements for assembly robots.

Pressure Sensors:

This sensor is used to measure the pressure of fluids or gases in an industrial environment. It is vital to maintain the correct pressure for the product quality or safety of the crew.

Temperature Sensors:

The temperature of the component indicates if they are failing or overheating. This can allow the maintenance crew to replace the fault before it results in expensive mechanical failure. Temperature sensors also monitor the ambient temperature to assure the quality of the product or food safety. Instant alert of a cooler going over-regulated temperature helps in saving the unplanned cost of food waste.

Humidity Sensors:

Balanced moisture can be an essential factor contributing to the final product quality. Monitoring the moisture guarantees that quality standards are always fulfilled.

Humidity also degrades equipment, so this sensor can inform the team if the humidity level gets disturbed. It is crucial to maintain the required moisture to enhance sensitive equipment’s life.

Level Sensors:

Level sensors alert the team if the fluid or solids level goes down. In this way, it ensures that hoppers are filled before they run out, and production time is not lost.

Acceleration and Vibration Sensors:

It is crucial to monitor the movement of equipment to know the accuracy or need for machinery maintenance—excessive vibration in the machine indicates loose bolts or worn-out bearings or motors that are about to fail.

Sound Sensors:

The pitch of some machinery also indicates whether it is operating correctly or not. By observing the machine’s pitch, the maintenance crew can be informed if the machine is running too high or low and needs repair or replacement.

With the evolvement of IIoT technology, major industrial sensor manufacturers are designing “smart” sensors. These sensors are easy to implement than analogue ones (as it requires PLCs to process and interpret data protocol). A smart sensor is able to process data within the sensor and transmit it directly back to the managing platform. This causes data transmission to be more versatile and saves bandwidth by just sending helpful information.

IoT Sensor Connectivity

IIoT deployment may involve a few or thousands of sensors monitoring and controlling a single machine or an entire production line. Sensors need to be connected to send back the data to the network and cloud software. This connection can be wireless or wired, and each of them comes with some form of pros and cons.

Many manufacturing plants opt to hardwire their IoT devices using industrial Ethernet cables. Hardwiring can guarantee a reliable connection, but the distance between sensors, I/O blocks and PLCs can limit its function. There is also the risk of damage to the cable, which comes with the cost of replacing it.

Nowadays, wireless IoT sensors are in trend as wireless are more powerful and reliable. It can cover a much larger area and distance. It is more scalable as many sensors can be deployed through this.

For instance, a single private LTE network can wirelessly connect many devices on a factory floor and provide seamless functioning.

How Are Manufacturers Improving Productivity?

Here are some examples that prove that IoT sensors play an essential role in helping manufacturers save costs and improve productivity.

Enhanced Product Quality:

In machines already connected to the cloud platforms, it is easy to store data such as temperature and pressure to track in production batches digitally. Machine vision via high-resolution cameras is another way of tracking products through a production line. Vision sensors with software can monitor product quality. Hence, this technology can reduce poor-quality products from reaching consumers who can imperil the company.

Minimize Unplanned Downtime with Predictive Maintenance:

The accessibility to real-time data and cloud-based analytics allows engineers and maintenance crew to spot inefficiencies in machinery. It is more valuable than scheduled maintenance, in which programs can analyze data collected from sensors to predict if an unplanned breakdown will occur or not. This ultimately helps technicians replace components before they fail, dodging any accident or expensive repair.

Warehouse Management and Asset Tracking:

In a smart warehouse, the IoT sensors can help track the flow of assets throughout the factory. Autonomous robots can pick or move or pack orders without human interference. Automating these tasks can allow employees to focus on other priority tasks.

Improve Procurement and Forecasting:

Sensors can also be helpful for procurement managers. Sensors installed on the production line can watch the assembly of products, help control raw materials usage, and reduce waste. It also alerts the crew when the supply goes down. Thus monitoring these essential items using sensors can reduce waste and enhance forecasting.

Product Development:

We all know that product development is one of the most critical and costly processes in manufacturing. Manufacturers can reduce the sum and make a better decision before concluding on total production.
One of the best ways is to gather data through sensors on the production floor and advanced manufacturing analytics to reduce the time consumed in the R&D process.

In fact, sensors on products can be implemented to collect data in real-life scenarios. Collecting data in real-time allows engineers to make rapid changes to get a more efficient product.

Summary

It is apparent that sensors plan a crucial role in daily operations throughout factories. Data collected using sensors can help develop a more efficient production line, machine operation, and safety.

How Bioengineering and IoT can Increase Agricultural Production

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April 11, 2022

How Bioengineering and IoT can Increase Agricultural Production?

Today, the Internet of Things is involved in almost everything, which means it is becoming part of every sector, industry, and daily life. Everything would be entirely in vain if we did not utilize this otherworldly technology for the betterment and improvement of agriculture.

We all know that with the increasing population, we need to improve the agriculture industry to meet the primary demand of every individual. Till now, with the help of digital technology, we have been able to solve some of the most significant issues existing in society, including food insecurity which is prevalent across the world.

Combining IoT, bioengineering, and urban farming methods can be a perfect and situation-meeting solution to enhance agricultural production in developed and undeveloped countries. Modern food production methods are already failing to meet the rising demands. So, it has become high time for all the agriculture industry leaders to focus on it.

We all know that the large-scale farming that is crucial to feeding an ever-increasing population is complex and challenging in a number of ways. On one side, agricultural production on a large scale causes a terrible effect on the planet through greenhouse gas emissions, deforestation, and the use of monoculture. On another side, a sudden pest infestation or disease can damage entire crop fields and contaminate the soils for years.

As per the research conducted by the United Nations (UN), the world’s population will exceed 9 billion by 2050, which means the requirement for 60 per cent more food production to feed everyone. The UN further states that sustainability is a critical component in handling agricultural systems and production in the future. In order to overcome the challenges and meet the needs, agricultural systems managers are trying to reach solutions by switching to technologies.

Using bioengineering, IoT, and other technologies can increase plants’ longevity, distribution, and even natural resistance against different diseases.

What are the Challenges for Agriculture Industry?

We all know the importance of the agricultural industry. The introduction of agriculture replaced the traditional nomadic cultures and planted the seeds for modern society. The earliest farmers domesticated plants and animals, and with the time being, high crop yield evolved.

In the 21st century, monoculture evolved as a low-cost, high-yield method of agriculture production. Though it provides enormous benefits, still it brings many problems like:

The adoption and practice of monoculture involve the continuous plantation of the same crop in the same field for years, reducing the soil nutrients.
Monoculture farms are also vulnerable to pests and disease, which sometimes damages the total yield in a single infestation.

However, bioengineering can help in disease eradication; at least, it has been proven in human beings. As per reports published by the University of California Riverside, scientists have been using bioengineering to stamp out deadly diseases like malaria.

For instance, when genetically modified mosquitoes were released into the wild, malaria cases decreased by 37 per cent. Similarly, bioengineering technology can be employed for agriculture production by leaders in the industry to reduce disease and eradicate pests.

Analyzing Data and Bridging Gaps with IoT:

Innovative bioengineering methods are helpful but cannot eradicate hunger without help from the agricultural IoT. Data shared by IoT can provide valuable insight into what can work and what does not in different locations worldwide. Agricultural sensor technology is already part of countries like Germany, China, and the United States, and we have gathered a lot from the information provided by IoT connected devices.

Smart agriculture devices gather data, from soil quality to moisture content, and it even monitors livestock health. Sensors attached to the equipment can monitor the health of equipment to ensure that machines are running correctly and do not face any mechanical issues. Farmers can use sensors to identify the potential source of waste like water and pesticides and can utilize the data to make informed decisions to reduce unwanted costs without negotiating with the health of the soil.

Sensors, along with IoT connected devices, can be beneficial for the agriculture industry as they can streamline the process of food from the farm to the dining table. Distribution of the produce is also essential, and IoT helps in this process also.

Reducing food insecurity in urban areas:

Food insecurity is becoming a prominent expression globally, but it can differ at different locations. Generally, city people are not in touch with nature and are deprived of natural food sources; and it is necessary to provide healthy food access to the ever-increasing urban population. With the integration of advanced technology like IoT and bioengineering, some agricultural industry leaders are looking for a solution, and urban farming has come up as an option to combat food insecurity.

For example,
San Francisco has become an example of feeding urban populations where at an indoor farm run by Plenty Inc., crops are grown in a carefully managed environment equipped with plenty of sensor monitors. To save space, crops are planted vertically rather than the traditional way that is in garden beds. Upon harvest, the bulk produced is distributed and sold locally.

Conclusion

The agriculture industry is broad and more complicated than one has imagined. However, advanced technology like bioengineering is at the vanguard of change for agricultural production. Farmers and agricultural industry leaders can utilize data from IoT to make better-informed decisions which ultimately improves crop production and potentially improves public health.

Maximizing AI and IoT Business Value While Protecting Customers privacy

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February 21, 2022

How to Maximize AI and IoT Business Value While Protecting Customers Privacy

Today more than 9 billion devices potentially utilize Artificial Intelligence (AI) and the Internet of Things (IoT). No enterprise or individual is untouched by the influence of these latest technologies. They are using it through their smartphones, applications, cloud services, sensors, RFID systems, and various other means. These unparalleled opportunities are skyrocketing business operations and constructing deep customer relations.

But all these benefits come with a situation that every business needs to address appropriately. Many business owners and executives prioritize customer privacy and security while utilizing exceptional opportunities of AI and IoT, and all this is possible through CIAM.

CIAM to Maximize Business Value

CIAM, Customer Identity and Access Management, is a sub-category of identity and Access Management (IAM)that aids in improving customer experience and security concurrently. CIAM integrates digital identity-based authorization with authentication to customer-facing applications. Businesses can opt for CIAM solutions either on-premises or as-a-service. They can cause it through interconnected identity APIs on web services and applications.

As per IBM Security, today, about 80 per cent of organizations are facing security breaches, and they stated that cybercriminals targeted customers’ personally identifiable information that is PII.

As per them, a compromised security breach on average costs approx $150 per customer. Thus, management is an essential security measure every business should add. There are four primary things CIAM does when implemented.

It facilitates customized authentication mechanisms for enterprises and their customers.
It improves the customer registration and login experience by reducing the risk of a data breach or account hacking.
It generates scalability regardless of the customer headcounts.
It Impacts AI and IoT amid expanding Security and Privacy Demand.

We all know that AI and IoT will be flowering in the coming decades. Businesses are trying to utilize these technologies properly to improve business techniques and methods. IoT promises to produce new mechanisms that can streamline business operations and boost customer experiences with the increasing business workload and hiking competition.

On the other side, AI is carrying a revolutionary change in time-consuming and tiring manual jobs by automating systems. It can also extract insight from granular customer data to enhance business efficiencies and create better customer engagement opportunities.

AI and IoT are the leading technologies that support modern business. However, these come with the concern of data privacy and security. Collecting and processing data using modern technologies might compromise customers’ privacy. But organizations that respect customers loyalty and trust use essential privacy protection techniques. Organizations can raise their standards and services from their competitors by benefiting from CIAM and privacy maintaining management systems.

Security and Privacy Challenges arising from AI and IoT:

Most progressive organizations need AI and IoT to expand and know the growing sensitivity of customer data privacy. Regardless, the dawn of AI and IoT drags in security and privacy challenges jiggling user trust.

IoT Security Challenges

With increasing IoT system connection, evolution, and expansion across any industry or organization, it becomes challenging to keep data and communication safe and secure. IoT is still in the blooming stage, along with its communication protocols. Business executives and customers find it challenging and problem-alluring to benefit IoT systems due to internet-based software attacks, authentification flaws, network-driven attacks and hardware attacks.

Connecting Data in AI and IoT systems

Organizations struggle with growing pains in adopting these technologies because of privacy reasons. IoT devices are implemented in sensitive areas like the healthcare, pharmaceutical and finance industries. Without securing the authentication of employees and customers, the entire system data and privacy could face significant risk. Thus, it is essential to ensure the security of an organization’s and its customer’s data while churning the best AI and IoT.

Inadequate User Experience with Conventional Security Tools

In IoT, user experience is highly non-interactive. Customizing IoT systems for excellent user experience without compromising security and privacy is complicated in legacy systems. The authentification mechanism in IoT devices does not provide a user experience. Lack of user experience affects the business value of AI and IoT-driven systems.

Disadvantages of Legacy Security Measures

An organization that use AI and IoT systems deploy security and privacy controls to mitigate the challenges mentioned above. There is no doubt that these legacy security measures can reduce data breaches, identity leaks and control access management but at the cost of lowering the potential of AI and IoT. They might mislead that adopting AI and IoT technologies are unsafe or risky.

As per a report, senior executives and managers are concerned that AI and IoT might expose customers and employees to strict privacy, ultimately reducing the potential of AI and IoT usage in the future. These hurdles will sustain for a long time until organizations switch from legacy security approaches to CIAM solutions.

Advance CIAM solutions enables AI and IoT integration without hammering user privacy, security, and user experience. Organizations can leverage CIAM solutions that align with the business guidelines yet provide cybersecurity and privacy protection while customers interact with IoT devices or AI-enabled systems.

Integrating CIAM Enabled AI and IoT

Security researchers and CIAM providers support customer identity and access control solutions while dealing with IoT and AI-driven systems. Such effective solutions help manage the challenges of governing, managing, safeguarding customers’ access to sensitive data. CIAM is necessary to balance AI and IoT-driven organizations with customer identity management. CIAM solutions double-shield the security by facilitating MFA, SSO, social identity-based login, PIN, etc.

CIAM solutions also have classically-minted IoT authentication methods and AI-based intelligent login procedures that enhance user experience that help in strong protection upon account takeover and data privacy without negotiating with user experience.

CIAM can provide tracking user consent, understanding and logging activities and helps in recognizing user preference at a granular level. It prioritizes customer privacy and security while generating a rich user experience in these static devices. It also aids businesses in deploying successful AI and IoT solutions.

Aligning Solutions

Organizations can manage or align CIAM solutions as per business policies. It can even analyze data extracted by AI or IoT sensors using predictive models while clearing privacy hurdles. It also emphasizes eliminating and removing data on demand when any customer ends the service or relationship.

Here are some essential points that the CIAM solution displays at an enterprise level.

Adopting Solutions

Today organizations are embracing CIAM solutions. These CIAM solutions offer different authentication techniques and measures like two-factor authentication, social media identity as login, biometrics login etc. Furthermore, the CIAM solutions also provide the service of employee identity and access management (IAM).

Maturing

The maturity of CIAM solutions assists organizations in deploying AI and IoT systems without concern. Advance CIAM solutions have direct measures addressing AI and IoT-specific security concerns. Reports state that organizations using advanced and matured CIAM solutions are 33 per cent more potential to implement plans in deploying AI and IoT than organizations with low CIAM maturity.

Advancing

Advanced CIAM solutions allow organizations to overcome AI and IoT-related security challenges. As per reports, organizations having mature CIAM solutions are 26 per cent to 46 per cent more feasible to overwhelm AI and IoT-driven security issues.

Deploying

Deploying mature CIAM solutions supports the security teams to draft a solid plan. Organizations with progressive CIAM solutions are 20-52 per cent more potential to boost business value without impacting the user experience or privacy. Besides this, these solutions also minimize customer data breaches and produce insights from the granular data they gather.

Artificial Intelligence has different building blocks like Machine Learning (ML) and Natural Language Processing (NLP). Although AI can generate a range of insights into several CIAM processes, the start of CIAM systems requires organizational knowledge, policy setup and human interaction to gain value from AI.

IoT sensors and devices capture an immense amount of data, including device location and even status. Such data are primarily stored in cloud-based servers. The scalability and distributed data from IoT devices increase data mishandling. Such data breaches also cause corrupt authentication. Organizations can use CIAM solutions for better authentication, regulatory data collection, and compliance in such cases.

Running on Automation

Today, almost all industries have adopted automation, which means most things operate through AI and IoT. Business owners and executives interested in utilizing IoT and AI in full potential take precautions about customer data security and privacy without negotiating with user experience. Organizations must employ mature Customer Identity and Access Management solutions to integrate smart authentication and authorization. These CIAM systems offer omnichannel interactions and authentication along with track while managing granular user consent, preferences, and activities.

admin

September 20, 2021

How to Improve Your IoT Device Security?

The Internet of Things has turned out to be the most life-changing invention of the era. The concept of connected devices has simplified day to day life and has upgraded the word ‘comfort’.

Internet of things has penetrated in every section, and with time it will become the spine of all the ruling industries. From smart mobile to smartwatch, from smart energy grids to IoT enabled industry machines, smart houses to smart towns, smart bicycles, smart hospitals, smart buildings, smart fitness trackers, smart refrigerators, smart medical sensors, smart security systems etc. If you see around, you will find out how things are becoming smart day by day, promising more comfort and less ambiguity.

We can simply celebrate the idea of establishing a network of things or physical objects embedded with software, sensors and technologies to connect and exchange data with other connected systems or devices over the internet that has become an idea of the century.

But, to protect this virtual network of physical objects or devices, we have to ensure robust IoT security because it helps shield connected networks and IoT devices. IoT security guarantees that any connected device, smart TV, smart refrigerators or smart locks, etc., is safe and free from hacking.

If IoT security work is executed precisely, it will be challenging for hackers to control IoT devices and steal the user’s digital data.

Let’s know how IoT security could be strengthened to establish a more secure and protected connected future.

Risk-Based Strategy:

A risk-based strategy is a mindset that empowers you to enhance the certainty of achieving outcomes by using techniques or methods that recognize threats and opportunities. This approach can be used during operations while designing the product or at product improvement stages.

Besides this, a risk-based approach also enables you to seize opportunities and skips from losses and enhances the entire working system throughout the organization.

Thus, we can easily conclude that considering a risk-based approach should be the main element of quality management systems, performance excellence processes, including ISO 9001:2015. The risk-based approach also helps you know the risk model of devices, and you can implement relevant security controls in an IoT system.

Updation of Firmware & Software:

IoT security requires timely updating of firmware and software, improving safety and offering plenty of other benefits.

For instance, timely updating software and firmware help repair security loopholes that might happen due to computer bugs. The updated process is meant to revise all the features present in IoT devices and allow you to add or update features to IoT devices and remove the older ones. Updating also allows your operating system to run on the latest version. Suppose, if you don’t opt for updating or renewing your IoT connected devices, then things might turn opposite, and you might not enjoy many benefits in your business.

Well, updating process requires some IoT security testing services to eliminate any kind of security issues within the IoT ecosystem.

Nevertheless, several IoT testing techniques like threat modelling, firmware analysis, protocol testing, incident response testing, etc., offer more stable and robust solutions.

IoT Device Security Features:

If you own a small connected device or having a complex IoT device network, then try to match the specific security criteria with IoT security testing.

IoT has seven fundamental characteristics; based on your need, you can perform testing to ensure that all device features are working correctly, bug-free, and free from all hacking risks.

Connectivity: In IoT devices, everything is connected, from hardware, sensors, electronics to systems; this means one has to ensure that connected hardware and control systems are able of making connections between various levels or not.
Things: Your IoT enabled device may comprise different sensors or sensing materials that need to be attached to appliances and items properly.
Data: We all are familiar that Data is the adhesive of IoT, and it is determined as the primary step towards action and intellect.
Communication: IoT enabled devices are connected with one or more systems; thus, this allows data to communicate while transferring or sharing through devices. In fact, communication is not limited by distance; it can take place over short or long distances. Let’s take the example of Wi-Fi. We all know that Wi-Fi is simple to connect with software for audio or video calls. Thus, in IoT, the data transferred from one place to another need to be analyzed and tested.
Intelligence: IoT devices hold sensing capabilities, or we can call Intelligence, and this capability is gained from Big Data Analytics and Artificial Intelligence.
Action: It can be defined as a consequence of Intelligence, and it can be based on manual interpretation or debates. For instance, in a smart factory, automation assists in taking important decisions to create more profits and reduce errors.
Ecosystem: It can be described as a place of the Internet of Things that connects to other communities, technologies, the picture, or goals the IoT can fit. The characteristics mentioned earlier of IoT should be considered while evaluating the security of IoT devices. Besides, following these characteristics enables you to check the security abilities to assure that IoT product is good to use.

Furthermore, monitoring for factors allows you to establish specific answerability and responsibility lines for the IoT ecosystem.

Automate Security Whenever Possible:

We all know that there is a considerable demand for connected devices and endpoints. Therefore IoT deployment raises the need to identify the threat, monitor data and other related security levels.

However, the main goal of automation within the development stage will remain the same: to check the security.

Thus, it becomes necessary to check every feature of IoT devices to provide maximum protection to the user.

Data Encryption is important:

Sometimes, it is observed that many companies face a challenge in storing their data in an encrypted format. However, data encryption is the best option to improve IoT security as data will never be transferred in plain text. One can even go for an alternative option like VPN to protect confidential data if unable to encrypt data.

Conclusion

Internet of Things is serving more than expected; most enterprises leverage it to improve staff productivity and reduce human labour. IoT is a futuristic gateway to assure the potential use of resources and assets, the effectiveness of operations management, cut off operational costs, enhance customer services etc.

So, if you are planning to embrace IoT to achieve your business goals, then focus on improving the security of your devices first.

How are Wearables Improving the Connected World Concept

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August 4, 2021

How are Wearables Improving the “Connected World” Concept?

Today, if we look around, we can easily sense that we live in a connected world ruled by sensing technology and intelligent devices. Every organization is attempting to climb the connected ladder between brands and customers to launch the most efficient and innovative product in the market. Few Research Centre took a survey and shared that wearable is the most popular smart device as one in five Americans owns it.

Wearables are changing the way of communication, monitoring and sharing information between consumers. They are playing a pivotal role in progressing the concept “connected world” we are living in. Even after having many desirable features, the overall wearable market has not hit dynamic market growth as analysts predicted.

Ericsson shared that almost 1 in 10 wearable users no longer use their wearable devices, and one-third have already abandoned them after a couple of weeks. The main reason behind this unpredictable behaviour is that consumers do not know what they need.

For lifestyle purposes or health reasons, customers try wearables as an experiment or eagerness and forget about it if they are unimpressed by the inadequate functionality of the connected device. On the other hand, instead of investigating the customer’s requirements or addressing customers’ needs, brands are just throwing products out to the market to know what functionality is beneficial and marketable.

One of America’s renowned multinational technology and e-commerce companies recently announced a catalogue of half a dozen different smart wearable products.

Based on the people’s curiosity and past experiences, researchers still conclude that wearables could make their place in the market. International brands are aggressively working to produce wearables that can stick in the market.

The COVID-19 pandemic hit has also caused a significant impact on the wearables market. Gartner shared about the shift in the choices of people amid COVID. In 2020 wearable market saw a momentary push in heath wearables which concluded that customers and vendors are more interested in health-focused wearables.

Therefore it is pretty clear that niche products do not meet customer needs. Consumers are looking for multi functionalities in a device or say “all-in-one” wearables are winners. But to develop such wearables, there is a need for more functionality, low energy consuming sensors and other latest technologies.

Sensing the Wearable demand

IDC predicts that there would be over 55 billion connected devices globally by 2025. This implies that every person on earth would own seven or more connected devices. The entire design should have the right factor, along with portability and user-friendliness. At the heart of this design are embedded sensors.

From consumer wearables that support a healthier lifestyle to medical wearables that help decide a patient’s vital signs by sensing components promptly are some of the advanced help these technologies offer to lives, consumers enjoy the safety, productivity, and health incentives.

The embedded sensors allow complex interaction between people and devices, enhancing the user experience to make daily interactions with smart technology more comfortable and natural. These sensors make it feel like the devices around us intuitively understand what we want them to do. Important needs of embedded sensor technology for connected devices are small size and low-power consumption and overall ease of ‘wearability’ for added comfort and functionality.

Small and low energy consuming sensors offer the best way of tracking a person’s health, physical activity, exercise; RF components assure the best connectivity and location determination, and wireless charging makes everyday life much simple, and it is almost as if the devices “charge themselves.”

The most crucial feature of sensor technology is to make our lives more convenient through seamless, simple interactions between people and sensing devices so that users can emphasize their other essential works.

It is evident that with an advance in wearable industries, there will be a requirement for more accurate, reliable and compact sensing technologies for long-term functionality in wearables.

Functionality comes with Challenges

Consumers expect “all-in-one” smart devices, and wearable devices are moving towards that. From texting to calling, timekeeping to vital monitoring is becoming part of today’s wearables. However, adopting this “new standard” carries challenges and issues with wearable battery life and power management structure.

No doubt, it is tough to compact multiple sensors for capabilities into a thin, small and lightweight device. The addition of new functionality drags a challenge of power management.

Ways to overcome efficiency issues include:

By transferring data wirelessly by using LoRa, NB-IoT, etc.
Unloading high power functions to solutions like Bluetooth Low Energy (BLE).
Selecting an effective microcontroller (MCU) for power management purposes to reduce power consumption – especially when the device is not in use.
Utilizing pin-type charging or wireless charging rather than a USB plug-in connection.
Improving overall sensor technology.

Wireless power is becoming part of a multifaceted world of small things. Designers demand a highly integrated semiconductor solution with minimum loss rates, robust performance, and outstanding linearity.

Boosting Battery Technology

Battery life is the most significant barrier to the growth of wearable tech today. Smart wearable devices need efficacious power management to run many various functionalities at once. Customers demand batteries that last for a long time and are easy to recharge. Most wearables have lithium-ion (Li-ion) or Lithium-ion polymer (Li-poly) batteries; these conventional batteries only fit basic on-functionality wearables with simple sensors and low power capabilities. They are unable to keep up with the demand of adding more functionality to a single device.

In the end, it’s the solution that is evaluated no matter which battery is installed in it. Semiconductor companies are endeavouring to address this need for new battery alternatives by designing battery management technologies, especially for wearables, instead of new battery technology.

What About Security?

Tracking health and location details, collecting personal and contactless payment information are some of the uses of wearables in daily life. Wearables are immensely collecting sensitive user data, causing security issues to the forefront, especially IoT security.

As per the report shared by Nokia’s Threat Intelligence, the percentage of IoT infections increased by 100%in 2020 and IoT devices make up 32.7% of the total infected devices now.

Wearables are an extension of the user’s smartphone; both devices create a significant security risk for the customer and connected wireless network if not secured properly. If a wearable or mobile phone is connected to a public network, it could be at high risk of valuable information piracy if the security infrastructure is not updated. It could be a great chance for hackers.

Currently, there is not enough space to improve security measures in wearables due to their small form factor. However, manufacturers are adding two-factor authentication, facial recognition, active sensing, and fingerprint sensing to shield wearables from end to end thoroughly to maintain security.

Safe, guarded, and efficient high-value semiconductor components will support IoT in the connected world.

IoT Connectivity Future

Wearables will speed up the merge of the digital and physical world. PwC highlights that wearable technology has just started influencing enterprises; in the coming future, semiconductor companies will lead this enterprise charge by delivering a better and high-value semiconductor for the fast-growing IoT application. With the availability and integration of more intelligent technology like artificial intelligence, connected devices will become more automatic, providing a world where our devices take better care of us.

How is IoT Making Buildings Smart and Efficient

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July 21, 2021

How is IoT Making Buildings Smart and Efficient?

Internet of Things is making space for its growth in almost every sector. We can say that the day is not far when the Internet of things will become a primordial need of every industry. It has just not changed the outlook of the manufacturing or retail or logistic industry or dairy but is contributing in enhancing the profits as well as helping in providing better service to customers.

So, today most of the sectors are willing to adopt the most innovative technology, i.e. IoT, because of the favours and benefits provided by it. As per surveys, the global IoT market would grow by $421.28 billion during 2021-2025 — a CAGR of 33% and $8 billion in 2019 to $19 billion by 2027 in the construction industry.

Well, if we talk about managing facilities and buildings, you might take some time to calculate the work and task and feel burdensome. Maintaining facilities in a building requires effort and cautiousness because a bit of delay may end up in an unhealthy environment along with disappointment.

So, let us see how IoT applications are helping in managing facilities and buildings.

Today, facility managers have to work proactively to stay competitive and ahead of the curve. They should have knowledge of technology and innovations. They should offer new digital services and ensure that their buildings are adapted for the future while ensuring the most reliable environment for everyone who will be using it.

Let us check some of the ways through which IoT is improving buildings and facilities.

How is IoT improving facility management?

Internet of Things-enabled devices can improve facility management and make premises a better place for employees and everyone else working with the organization.

The advantages of including IoT in building management are:

IoT reduces operational costs by creating cost-effective, energy-efficient buildings that operate efficiently and handle resources in the most optimal way.
IoT keeps employees safe and healthy by encouraging clean, tidy, and hygienic environments that are regulated and cleaned as per the need caused by the constant movement of humans.
IoT promises to maximize productivity, ensuring all team members have everything they require to complete their tasks and stay relaxed and concentrated all the time.
IoT devices ensure safety and risk mitigation; they detect risk areas, automate relevant action, and keep physical and digital assets safe and secure as long as possible.

Facility Management Examples:

Managing Desk and Workplace Occupancy using IoT:

As the COVID-19 pandemic has hit globally, one of the biggest challenges was running a business to sustain the economy. Most of the organizations and companies adopted the startling trend and provided remote employment. There is a massive rise in remote working, i.e. from early COVID-19 to March 2021; remote employment increased from 15% to 70%.

It is supposed that this work from home facility won’t be a temporary change- about half of the employees expect this work from home culture would continue for them into the near future, and 31% believe it will be permanent.

Internet of Things can support businesses in managing their premises effectively and efficiently during this challenging time. In coming years occupancy can fluctuate between days as we move towards a model where employees will join the office a few days each week.

IoT enabled devices such as sensors attached to desks can trace, predict and inform office occupancy. It creates digital plans that would allow employees to find space promptly. It offers the tools to optimize the existing space by grouping desks as per the need of the office. IoT even saves energy and helps in freeing up space for new uses.

Air Quality Monitoring using IoT:

Air quality issues have been a significant concern, but pandemics brought this issue into the spotlight. Air quality and proper ventilation have always been a priority concern in offices. Before COVID-19, poor ventilation has caused:

Easily disease developed
High possibility of respiratory diseases such as asthma
Allergies
Headaches
Nausea
Dry eyes

Improper ventilation also impacts productivity- one study saw that poor ventilation at the workplace decreased employees’ cognitive ability, making them perform worse at their jobs and decreasing their productivity.

One of the best solutions to this issue is adopting IoT devices to measure air quality conditions such as humidity, temperature, CO2 levels, etc. This feature enables pinpointing the areas for concern and taking relevant actions to create a safe and healthy environment for employees which ultimately improves productivity for the entire team.

Washroom Monitoring using IoT:

A clean washroom is a priority and no doubt, keeping a restroom clean in a busy office with limited cleaning staff and resources is challenging. Keeping the washroom tidy is an essential part of managing a pleasant, healthy and safe environment.

Thankfully, IoT is a saviour in this situation also. IoT devices can track the washroom business, enabling the prediction of when rooms will require cleaning and how many times in a day.

Thus, one can allocate a building’s cleaning resources more efficiently and help cleaning staff spend time more effectively. Therefore, this helps develop a cleaner and more enjoyable environment for employees in the organization and reduces extra expenditure and saves resources.

Conclusion:

Smart buildings hold a great scope in future. IoT is becoming part of every sector. It is widely used, more affordable and can manage a wide variety of jobs. No doubt it will soon become part of the furniture in offices and other commercial building globally.

We can doubtlessly say that IoT technology is ideal for facility management and brings the smart building revolution. It just not benefits the organization but also take care of employees. It smoothens the working process of the organization without compromising on quality.

If you become a part of this expanding trend now, you’ll be capable of managing your facilities in the most effective, productive and cost-efficient way. But if you are still in a dilemma and choose to work using the old-tradition method, you might face failure and loss.

So, don’t waste your time and become a part of this trend.

admin

May 26, 2021

What are the challenges with Big Data Analytics in IoT?

A successfully running IoT environment or system embodies interoperability, versatility, dependability, and effectiveness of the operation at a global level. Sift advancement and development in IoT is directly affecting data growth. Multiple networking sensors are continually collecting and carrying data (say geographical data, environment data, logistic data, astronomical data, etc.) for storage and processing operations in the cloud.

The initial devices involved in acquiring data in IoT are mobile devices, public facilities, transportation facilities and home appliances. The flooding of data suppresses the capabilities of IT architectures and infrastructure of enterprises. Besides this, the real-time analysis character considerably affects computing capability.

The generation of Big data by IoT has disturbed the current data processing ability of IoT and demands to adopt big data analytics to boost solutions’ capabilities. We can interpret that today success of IoT also depends on the potent association with big data analytics.

Big data is recommended for a thick set of heterogeneous data present in the unstructured, semi-structured and structured forms. Statista shares that big data revenue generates from service spending, representing almost 39 per cent of the total market as of 2019. In 2019, the data volume generated by IoT connected devices was around 13.6 zettabytes, and it might extend to 79 zettabytes by the end 0f 2025.

Big Data and IoT

Big data and IoT are two mind-blowing concepts, and both need each other for attaining ultimate success. Both endeavors to transform data into actionable insights.

Let’s take an example of an automatic milking machine developed using advanced technology like IoT and Big data.

Automatic milking machine software is designed by Prompt Softech. The Automatic Milk Collection Software (AMCS) is a comprehensive, multi-platform solution that digitizes the entire milk collection system. All the data is uploaded on the cloud, which provides real-time information on milk collection to the stakeholders.

AMCS enables transparency between dairy, milk collection centre and farmers. The shift from data filling on paper to digital data storage has reduced the chances of data loss along with human errors. A tremendous amount of data is processed and stored in the cloud daily. On the other hand, farmers get notified about the total amount of milk submitted and the other details. They can access the information about the payment and everything using the mobile app at any time.

This combination of real-time IoT insights and big-data analytics cuts off extra expenditure, improves efficacy and allows effective use of available resources.

Using Big Data:

Big data support IoT by providing easy functioning. Connected devices generate data, and it helps organizations in making business-oriented decisions.

Data processing includes the following steps:

IoT connected devices generate a large amount of heterogeneous data stored in big data systems on a large scale. The data relies on the ‘Four “V” s of Big Data: Volume, Veracity, Variety & Velocity.
A big data system is a shared and distributed system, which means that a considerable number of data records in big data files are present in the storage system.
It uses an excellent analytic tool to analyze the data collected.
It examines and produces a conclusion of the analyzed data for reliable and timely decision-making.

Challenges with Big Data Analytics

The key challenges associated with Big Data and IoT include the following:

Data Storage and Management:

The data generated from connected devices increases rapidly; however, most big data systems’ storage capacity is limited. Thus, it turns into a significant challenge to store and manage a large amount of data. Therefore, it has become necessary to develop frameworks or mechanisms to collect, save, and handle data.

Data Visualization:

Usually, data generated from connected devices are unstructured, semi-structured or structured in different formats. It becomes hard to visualize the data immediately. This implies preparing data for better visualization and understanding to get accurate decision-making in real-time while improving organizational efficiency.

Confidentiality and Privacy:

We all know that every IoT-enabled devices generate enormous data that requires complete data privacy and protection. The data collected and stored should stay confidential and have complete privacy as it contains users’ personal information.

Integrity:

Smart devices are specialists in sensing, communicating, information sharing, and carrying analysis for various applications. The device assures users of no data leakage and hijacking. Data assembly methods must use some measure and condition of integrity strongly with standard systems and commands.

Power Captivity:

Internet-enabled devices need a constant power supply for the endless and stable functioning of IoT operations. Many connected devices are lacking in terms of memory, processing power, and energy –– so they must adopt light-weighted mechanisms.

Device Security:

Analytics face device security challenges as big data are vulnerable to attacks. Data processing faces challenges due to short computational, networking, and storage at the IoT device.

Many Big Data tools provide valuable and real-time data to globally connected devices. Big data and IoT examine data precisely and efficiently using suitable techniques and mechanisms. Data analytics may differ with the types of data drawn from heterogeneous sources.

Source: IoTForAll – Challenges with Big Data Analytics in IoT

admin

November 12, 2020

How is Artificial Intelligence Contributing to the IoT Revolution?

Today businesses around the world are extracting the potential outcome by deploying IoT in their business operations. They use it to create new and optimized business possibilities. The firm growth of IoT in various industries is spectacular, whereas AI and its influence on a professional and personal level are considered undervalued. However, combining IoT with rapidly improving AI technologies can design ‘smart machines’ that stimulate intelligent behaviours to make a precise decision without any human interference. Thus, AI-IoT together minimizes chances of error and ensures efficiency along with productivity.

How does AI help in the IoT revolution?

Artificial Intelligence performs smart tasks such as language translation, decision making, voice recognition, etc. and IoT involves a series of interconnected gadgets to transport information over a network. IoT gadgets depend on web connectivity to deliver a fair amount of relevant information about users such as user behaviour, users’ preferences, personal details, etc. It is absolutely wrong to overlook them as they contribute to improving the operations and user experience. However, many organizations have no idea about saving and processing of massive amounts of data which ultimately hinders the growth and potency of IoT.

In this critical situation, AI work as saviour as it helps to store the bulk of data processed by the IoT devices. It analyses and produces a sense of it. Thus, we can conclude that AI is a chief driver which promises to contribute to the exceptional growth of IoT.

Enabling evolving profits for businesses

Earlier, the AI framework was taking care of limited categories of the task. They were not scalable and required human interference. However, advancement in technology has created a successful transformation of AI by involving it into IoT concept. The collaboration of AI with IoT has introduced smart machines which require the least human intervention. The integration of two evolving technology will bring a dramatic change in different industries. Four significant changes that will emerge in businesses after integration of AI & IoT are:

Improved revenue:

Integration of IoT with AI will be profitable for many industries and sectors in terms of generating significant revenues and returns. IoT data providers, IoT gadget, manufactures and companies offering application services based on smart sensors will also enjoy the profits gained by the togetherness of these two highly effective technologies.

Better Safety Standards:

Un-interrupted and regular monitoring allows a business to take prompt decisions to restrict any failure. Up-to-date monitoring improves overall protection and security standards while enhancing productivity. The strict monitoring over different operations even reduces the possibility of harm to lives and assets.

Decreased Expenses:

Assessing the appliances by smart detectors, the sensor installed domestic devices and smart electricity meters cut the extra operational costs in businesses or household works.

Improved user experience:

Smart sensors offer a plethora of opportunities to improve the user experience. These detectors catch the user’s preferences and provide them with options accordingly. For example, smart ac sets the temperature as per the user’s need.

Positive influence on different industries

1) Manufacturing Industry:

Manufacturing sectors like aircraft, automobiles, mining, household appliances, etc. sync smart sensors with their machinery to get future analyses and improve efficiency along with productivity. Industries are endeavouring to develop a wholly autonomous and advanced industrial unit. The installed sensors will assist enterprises in detecting the areas with looming threats, informing about the future maintenance requirement to ensure least machinery falls.

2) Smart Homes:

IoT has introduced advancement in homes too. Today, smart home concepts have taken up speed. Smart homes concept means a house where all the gadgets are connected through a shared network. Integrating IoT with AI will enable devices to interpret the owner’s instruction and make smart decisions, respectively.

A smart home consists of technologies that aim to make lives comfortable by allowing the owner to regulate the device remotely, regardless of where she/he is currently present. It even ensures better safety and security. For example, an owner can pre-plan the time at which he/she wants coffee, or when TV should turn on to watch their favourite show.

3) Body sensors:

Smart detectors have made the lives of patients and doctors easy. These smart devices sense different activities to maintain good health. Today, pharmaceutical companies are investing in medical sensors that can assist patients in keeping a track on their health. In the covid-19 situation, most of the hospitals are offering virtual consultations to their regular patients. Smart sensors are tracking the health of patients and sending health alerts to the doctors if any changes appear. This technology has allowed everyone to follow social distancing to minimize the chances of Covid spread.

For example, sensors evaluate blood pressure, blood sugar levels, etc. and send a notification if any changes occur.

4) Airlines:

Sensors have also become part of the aircraft to monitor the looming risks and errors and to assure safety before any mishap occurs. These smart sensors predict probable errors and calculate the degree of severity to decrease aircraft downtime and ensure safety. Airline companies also use sensors to detect the maintenance issues that typically cause flight delay and cancellations.

5) Oil Rigs:

Oil industries have to spend a fair amount on obtaining oil drilling machinery. Oil companies can use smart sensors to get a timely notification for servicing and reduce the operational cost. Sensors attached to the machines provide the information about the condition of devices and send the alert for maintenance or servicing before any damage happens to a machine.

Wrapping Up:

IoT and AI are technologies which seem to complete each other through one or another way. This deadly combination will change the outlook of many businesses and industries. It will even improve our personal and professional lives in a very positive way. Thus, undoubtedly this ultimate combination is highly beneficial as it will open up new opportunities for growth and innovations—the addition of AI in IoT concept can ease the business processes, improve productivity and provides enhanced user-experience.

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