IoT Data

Big Data be Integrated into Your Business to Improve Output

How can Big Data be Integrated into Your Business to Improve Output?

Nowadays, information usage is soaring. This information, dubbed Big data, has expanded too large and complicated for typical data processing methods.

Companies are potentially utilizing Big data to enhance customer service, boost profit, cut expenditures, and update existing operations. This shows that the impact of Big Data on businesses is enormous and will remain impactful in the coming years.

But do you know from where these affecting Big Data come?

Big data is generated mainly by three sources:

Business:

Companies produce massive amounts of data on a daily basis. Some examples include financial data like invoices, billing and transaction data, and internal and external documents like business letters, reports, production plans, and so on. Big data generation is vital for enterprises transitioning from analog to digital workflows.

Communication:

Communication is the data that one generates as an individual. Social media blogging and microblogging are all vital communication data sources. A new photo, a search query, and a text message contribute to the growing volume of big data.

IoT:

Sensors integrated with IoT system produces IoT data. Smart devices use sensors to gather data and upload it to the Internet—for example, CCTV records, automated vacuum cleaners, weather station data, and other sensor-generated data. Overall, big data can be called massive data collections obtained from different sources. It can be utilized to find patterns, links, or trends to analyze and anticipate them.

Big data can be used to enhance security measures. Businesses and individuals use free VPNs and proxies to protect their data. They both depend on big data because it supports strengthening the technology.

Now, let’s get into the details of how businesses can potentially use big data to improve their operations and boost productivity.

How do businesses use big data?

Big data applications have multiple uses. Also, we can easily see various businesses employ the technology for different objectives. Insights collected are often used to make products and services more efficient, relevant, and adaptive for individuals who use them.

The applications of big data are:

Catching security defects:

With things getting online, data breaches and theft are among the most common problems as digital systems are getting complicated. Big data can be used to find out potential security troubles and analyze trends—for instance, predictive analytics catch illegal trading and deceitful transactions in the banking industry. Comprehending the “normal” trends permits banks to discover uncommon behavior quickly.

Comprehending more about customers:

This is one of the most critical and typical big data applications. Companies extract vast amounts of data to analyze how their customers behave and their choices. This enables them to predict the goods that customers desire and target customers with more relevant and personalized marketing.

One of the best examples is Spotify. The company also utilizes artificial intelligence and machine learning algorithms to motivate customers to continue connecting with the service. Spotify finds related music to design a “taste profile” as you listen and save your favorite tracks. Using this information, Spotify can suggest customers new songs based on their earlier choices.

Product invention:

Comprehensive data collection and client demand analysis can also be used to forecast future trends. Companies can utilize big data analytics to transform collected insights into new goods and services. It allows them to predict what their clients need. The corporation can offer data-driven proof for production based on customer demand, popularity, and interest. Instead of waiting for clients to tell their needs, you can fulfill their demands beforehand. Besides this, being more innovative than competitors is also a plus point for businesses.

Create marketing strategies:

Well, we are pretty familiar with the fact that a small marketing blunder can cost a lot to a company. A marketing that does not resonate with the target demographic might end up creating disaster. However, the availability of more specific data makes marketing more secure but complex.

This lets you gather information on how people respond to your advertising and allows you to create more personalized campaigns. This increased focus allows the marketing team to make a more precise approach, turn more effective, and reduce cost load.

Do you think big data is a big risk game in a business?

Till now, it’s very clear that big data provides enormous opportunities. Businesses flourishing in different sectors can take advantage of the available data. However, it could not be a smooth journey as various challenges are involved with this analytics method.

The accuracy concern:

This will also allow you to start combining data streamlining from a vast range of sources and formats. The challenge then comes to knowing which information is valuable and reliable and how to crack that information meaningfully. However, “cleaning” of data is a part of the big data sector; it is not without complication.

The price barrier:

Welcoming and adopting the world of big data carries several drawbacks. There are many aspects to be considered here- the hardware and the software. One must consider data storage and systems for managing enormous amounts of data. Furthermore, data science is increasing rapidly, and those who understand it are in high demand. The fee for recruits or freelancers can be high. Lastly, developing a big data solution that meets your company’s needs demands significant time and money.

The security challenge:

The challenge of safely storing such a large amount of data generated from collecting such a large amount. Therefore, Cybersecurity is another essential concern as data privacy and GDPR grow more vital.

The bottom line

We can easily conclude that Big data is fetching enormous benefits to many companies belonging to different sectors. Therefore, companies may thrive in the digital economy by effectively analyzing and managing flooding data. There may be many hindrances in integrating big data into business infrastructure. Still, the initial investment overcomes the rewards and advantages offered by big data and its potential application in the business. Therefore, spending time deciding whether to go for big data or not will surely land you at a loss.

How to Address Data Management Challenges in IoT Using Fabrics

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.

Smart and Sustainable Livestock Management supported by IoT

IoT-Enabled Livestock Management: A Smart and Sustainable Approach

Food is a basic need for every living being, and the importance of the agriculture industry and livestock farming cannot be underrated. The demand for food, rabbit and poultry meat, has been increasing day by day, and the reason behind this increase is population growth, changing diets, and affordability. This has led to an increase in the number of poultry and rabbit farms worldwide and improved the sensitivity toward animal welfare issues.

Many farm owners have adopted standardized farming management practices to meet the growing meat demands. Many others have added new technologies and innovations like smart farming methods using the Internet of Things and machine-to-machine solutions in their livestock management process.

Adopting the latest farming technology, smart sensors, and livestock monitoring solutions can assist farmers in efficiently managing their resources and enhancing productivity. This adoption also guarantees minimum wastage and less energy consumption.

Value Proposition

Traditional methods of livestock management include inspecting each animal for signs of injury and diseases. Farm owners with large livestock farms often fail to detect ill cattle and face loss. This monitoring method is time-consuming, labor-intensive, costly, and highly erratic.

As per research conducted by Oklahoma University, lung lesions and scarring are found in 37 percent of cattle that had never been diagnosed as sick, and in a trial at the Meat Animal Research Center found that 68% of steers tested showed signs of past respiratory infection.

Although the animals can recover independently, studies show that once cattle have been ill, they cannot catch up to the rest of the healthy herd in health or value.

IoT Data for Livestock Houses and Management

Farmers can optimize their processes, improve animal welfare, enhance traceability, and increase overall productivity by adopting IoT technology offering real-time data on environmental aspects like temperature, gas levels, and humidity.

Such IoT solutions are constructive for monitoring ammonia levels, which causes severe eye irritations and respiratory problems in animals and humans as well. By keeping these aspects under control, farmers can improve their cattle’s health and well-being and enhance the final product’s quality.

Enhanced Farming Practices

Using low-cost and durable smart sensors in an IoT solution for farming is an efficient and cost-effective way to gather and analyze data. The IoT sensors can be implanted in different locations around the livestock houses to gather data on different aspects like temperature, humidity, water quality, gas levels, and many other things.

The sensors can also be installed to gather data in real-time, guaranteeing that the farmer has access to real-time information about their farm’s current status, environment, and operations.

The consolidated and easy-to-install feature of the sensors makes them a feasible option for farmers who wishes to speed up their farming practices without disrupting their procedures. The advanced battery-backed system guarantees that sensors are durable, skipping the frequent battery replacement and maintenance requirements.

IoT Platforms for Livestock Houses

The gathered data is then processed and analyzed using an IoT platform, which can provide insights and actionable suggestions to the farmer. The information can be accessed using mobile devices, authorizing the farmer to monitor their farm from any location at any time. The data provided is in an easy-to-understand format means farmers do not need specialized technical knowledge to understand and utilize the information.

What are the Benefits of IoT-Enabled Livestock Management?

  • Monitor the health and vitality of livestock in real-time, allowing farmers to immediately treat animals and prevent the spread of illness or disease.
  • Track grazing animals to know their grazing patterns and activities and prevent loss. 
  • Collect and analyze past data to identify and understand trends in cattle health or track the spread of illness.
  • Monitor the heat period or birth time, avoiding the loss of new calves and optimizing breeding practices.

Revolutionizing the Farming Industry to Boost Productivity

The success of IoT in reducing disease and mortality rates in livestock houses, increasing output, and optimizing overall operations shows its potential for enhancing farming practices.

The data gathered using the sensors can be utilized to determine the pattern and make informed decisions to enhance productivity, lower costs, and guarantee animal welfare.

Overall, employing IoT technology in farming is the most futuristic approach to overcome the food crisis and counter the increasing demands of a growing population. It has the potential to revolutionize the industry and address some of the challenges encountered by farmers, like limited resources, growing demand, climate change, etc.

We all are very well aware of the significant issue of this era: climate change. The changing climate is hammering productivity and leading to the food crisis. On the other hand, the uncontrollably growing population is amplifying the issue. The only possible way to control both major issues is to adopt the most potent solution that can resolve both issues hand in hand. The adoption of IoT in farming is the most extensive way to overcome both challenges. Not only in farming, but IoT can also be used to control carbon emissions and contribute to slowing down the rapidly changing climate. IoT also helps provide a better lifestyle by offering smart houses, cities, buildings, hospitals, and the list goes so on.

How IoT Data Analytics Impact your business

What is the Impact of IoT Data Analytics on your Business?

Today, if we observe the trend and business processes, we can express that IoT solutions are changing the way of doing business globally. However, saying that all solutions provide equal benefits would be wrong. We can say that an IoT solution that shares data without analytics is like a symphony playing Mozart without a conductor. This means music is there but with no structure and loses its purpose, beauty, and meaning. We all know that there will be immense flooding of data by IoT, but the absence of a process to properly analyze the data would just cause complexity and noise without proper output.

The Impact of Data Analytics on businesses

Data is compelling and empowers by giving insights into all aspects of the business. It can assist organizations in refining processes, locating missing physical assets for cost saving, or even helping in defining new use cases for already available products. 

In the absence of data, a company can be just reactive or can assume future challenges and results. 

With the data offered by an IoT solution, a company can anticipate the emerging problem before it becomes complicated and resolve it as soon as possible. However, there are IoT data solutions that only offer the data and no other context to make it meaningful. In such cases, IoT analytics comes in as a savior. 

The capability to interpret the data before it comes in front of the user is compelling. For instance, data analytics can help alert a factory manager about the floor problem in real-time instead of waiting and then reading through reports on issues that have already happened. This can reduce time consumption and the possibility of errors. 

Analysis software is available in many forms, from one-size-fits-all products to low-code/no-code solutions to solutions that demand an experienced engineering team to execute and maintain.

Each type of solution has benefits and expenses, and your enterprise must determine the best-fitting solution to get the maximum benefit.

Well-known IoT Data Analytics Solutions

We all are aware that technologies like AWS IoT Analytics, on the one hand, are sophisticated and powerful but, on the other hand, very complicated to execute and demand a highly skilled engineering team having domain expertise. The advantages of the analytics solutions are- it offers customization. Everything needed in your business and unnecessary things to be left out. You can consider AWS IoT products like building blocks: you can get maximum from them, but they demand a lot of planning along with maintenance and oversight.

All businesses cannot afford or consider hiring an expert engineering team to execute these solutions. These businesses are inclined toward adopting a one-size-fits-all solution like Azure provides IoT Central

Azure even provides a solution analogous to AWS, but they are more successful in an out-of-the-box strategy. The straightforward analytics provided by this solution or any other one-sized solution can fulfill the requirements of many businesses. They enable businesses to connect promptly and design their dashboards and alerts within a few days or hours. If your business just needs simple alerting or has a limited number of devices to connect, then opting for this solution would be a great idea and cost-saving as well.

Customizable Solutions

The main challenge with the IoT data analytics solutions mentioned above is that they don’t provide customization options, are costly to scale, and might compel your team to do analytics using a third-party tool (which is no doubt another pricey option). Suppose you own a business having specific analytic requirements and many devices to be connected. In that case, a low-code/no-code solution, like the one proposed by Leverege (running on Google Cloud), could be a terrific middle-ground solution. This type of solution is customizable per the business’s requirement and, in parallel, does not need any technical expertise if it offers an end-to-end alternative and has analytics and an excellent alerting system, even without needing a dedicated and proficient engineering team. 

Irrespective of whatever solution you choose for a business to implement, ensure that a third-party tool to be integrated gives you maximum flexibility and value from the data. Tools like Power BI, Tableau, and Looker can be the best option to support your company in familiarly visualizing your data. If your company has already made a preferred analytics tool list, then it will enable your users to harness their expertise of that tool with new data sources.

Valuable Insights

Till now, hope that you have understood the importance and contribution of Analytics tools. It is essential to obtain the optimum value from IoT solutions irrespective of the products the business chooses. Neglecting these core capabilities may take your business to the loss side as it may miss valuable insights and maximize value. We can simply infer that IoT solutions, no doubt, enhance business operations but remain incomplete.

Data analytics gives direction and beauty to the solutions as it analyzes the data and offers favorable data to businesses to boost operations and amplify outcomes. Today, most companies are embracing the Internet of Things but are unaware of the importance of data analytics and ignore it. They face losses and then switch back to their old processes and operations. Therefore using IoT and offered IoT solutions must be opted for after attaining full knowledge.

Today, IoT is making its space in almost every sector, from smart homes to smart buildings, from smart towns to smart cities, and from smart farming to smart logistics; one can see the influence of IoT in every sector.

Similarly, data analytics is also contributing from its end to add more value to every solution offered by the Internet of Things. For instance, in the baking process, the availability of raw ingredients is insufficient, and it does not come together without a recipe. The recipe brings ingredients together in a beautiful way and offers the best. So, if you are still untouched by the magic of data analytics, then you might be losing a lot of benefits and leverages offered by it.

How IoT Boosts the Micro Mobility Market

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.

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.

IoT Data-The key to the smart connected world

IoT Data: The Key to The Smart Connected World

Today, imagination has the power to become real, and all this is possible through the Internet of Things. It has empowered humankind with the ability to convert vision, thoughts and imagination into reality. From smartwatch to smart Tv, smart building to the smart town, every impossible and futuristic dream is becoming part of day-to-day life. So, it is pretty clear that every connected product leads to almost endless possibilities, from enhancing products to creating synergies that almost seemed impossible in the past.

Businesses manufacturing smart products or using IoT to streamline efficiencies are dependent on one thing: data. Data plays a critical role in making the whole IoT system effective and efficient. The data points collected from connected devices communicating to one another create a tapestry of insights for organizations that hold the skill to efficiently and precisely curate and analyze them.

Let’s know about things more closely.

Smarter Products

Usually, there is a lot of guesswork with smart product development. Suppose we summarise the current tech status, then yes. In that case, we are still in the primary stage of IoT, especially in selecting the data connected product development though we are surrounded by an ‘n’ number of IoT connected devices and products. However, manufacturers are learning that smart products offer tremendous insight into which features are used the most, which are sometimes utilized and sometimes not.

No doubt, there is a wealth of information available on smart product relationships. Let us understand this by taking an example of a connected kitchen. In a connected kitchen, multiple devices interact with one another. The data collected shows the quantitative impact that connected products cause on each other, and in some cases, it even identifies relationships that have not been clear at first glance.

IoT data can inform manufacturers when something operates incorrectly, and which factor is behind the emergence of the issues.

For instance, it can check if it is an isolated incident, or the issue arises whenever specific factors leading to the problem occur? This information can highlight anything from fundamental performance problems to possible safety issues. The data permits manufacturers to analyze it and enable them to make intelligent updates to the product or develop a new one, or in some cases, it suggests discontinuing the product altogether.

Safer, More Efficient Production

To utilize the values provided by IoT data to the next meta-level, it is essential to check how connectivity can help in the development of smart products.

The Industrial Internet of Things, i.e. IIoT, is the next new thing of the IoT revolution. In the manufacturing sector, connected devices offer a wealth of information related to certain aspects of smart product development.

As discussed in the smart kitchen example, data from connected devices can inform managers about production delays and the possible reasons for this delay.

Suppose there may be lags from one stage of the manufacturing process to the next, and that may not be detected without the connected data.

Sensors attached to the devices also warn about the part of machinery that needs to be repaired or is about to fail altogether. This gives a manager the ability to address the issues before the fall down happens and prevents the possible production slowdown or failure.

IIoT data can also help in discovering possible manufacturing safety hazards, like dangerous interactions between connected machinery. Besides this, smart wearables can observe the health status of the employees working in the plant. It monitors the vital signs, which can signal possible health issues. By integrating past and present data, it is possible to improve the overall safety of the plant, which ultimately results in better results.

Thus it is clear that either for uniform operation or to ensure the safest possible work environment, IIoT data offers insights into managing a continuous flow of production, which ultimately plays a vital role in delivering a product to market and ensures fulfilment post-launch demand.

Getting Data Where It Needs to Be

Gathering data and churning valuable information from it is a significant step toward market differentiation. The connected devices offer extensive data, and it is crucial to segregate valuable data from the flooding data. 

Now, its time to know the three things that every organization needs to do:

  • Crush the silos: We are crossing the stage where each department had its own sets of data that never went beyond its four walls, and this whole system is essential as it associates with IoT data. The entire system of IoT data is dependent on how data interacts to produce new insights. Today, innovative product manufacturers who embrace IoT on a micro and macro level are the ones who will shine in the coming future and will benefit the most. They will ensure that appropriate data gets to those who want to use it.
  • Share progress updates: When disruptive new insights are available, make sure that stakeholders know them and demonstrate why insights are vital to individual departments as well as organizations. This whole process, which involves sharing information, ensures that everyone is aware of the overall status of the product and its current development stage.
  • Avoid oversharing: It is undoubtedly imperative to enhance data sightlines, but it should not overload stakeholders. There is an immense flow of data that might eat up time in making helpful reports, but it would lead to a delay in the project and might hit critical product development.

Wrap up:

IoT holds a great future; in fact, we can say that IoT is the future. Coming decades will be transformative for innovative product manufacturers who comprehend the art of IoT and its data analysis. These future-oriented companies will offer products featuring more personalized, powerful, and intuitive services than ever before. These IoT-based organizations will create a new digital ecosystem where everything will be interconnected and inform each other. So, be ready to see a world where devices communicate and offer the best possible assistance and solutions.

Why Your Organization Needs IoT Data-Based Maintenance Management

Why Your Organization Needs IoT Data-Based Maintenance Management?

IoT is nothing new, but it is not old even. It always comes up in the news with the new feature and allures everyone. Today, it is rare to find out someone who is not aware of the Internet of Things or its benefits. Small, medium or large, all size companies are thriving to become part of this beautiful and limitless technology. One who has already adopted it are enjoying immense success and benefits in their business.

How is significant IoT Data?

IoT data holds tremendous value to maintenance management functions, but no doubt, the quality of value is directly dependent on the quality of the data you receive. This implies that source, timeliness and accuracy greatly influence the overall value data can offer. If you are planning to create IoT data that can aid to materialize your business objective, then, you must find out the following aspects.

  • The first aspect is to find out the data type required to meet your objectives and the data you can quickly gather from machines or in the field. You might find the gap between the two data points and no doubt, overcoming this gap is a long-term goal that could be accomplished as the sensor and network technology modernizes in the future.
  • Now, you have to validate the available data on the aspect of reliability, accuracy and timeliness to find out the relevant data.
  • You have to build a CMMS software architecture that can interpret the appropriate data into information.

Let’s check how companies in asset-intensive industries are utilizing IoT to change their existing maintenance management functions.

Predictive Maintenance:

The best feature that IoT data can offer is predictive maintenance, and we can say this on the basis of two key reasons. The progress in sensor and network technologies allows IoT data to help asset-intensive industries to optimize their maintenance management functions.

The first key reason: IoT data permits you to predict maintenance requirements and asset failures. It provides you with enough time to schedule the most favourable field service technicians based on their availability and skill set. Thus the process is streamlined successfully.

The Second Key Reason: The data-driven ability to conduct maintenance scheduling on an ad-hoc basis saves time and reduces the cost and improves first-time effectiveness.

For instance, HVAC equipment has temperature sensors to monitor the airflow efficiency and sends alert for filter replacement or maintenance when the airflow changes. In the same way, sensors embedded in solar panels which are connected through IoT can generate work orders whenever required and as per the need.

Data-Driven Inventory Management:

Inventory is an essential part of the maintenance function. There are many organizations that are dependent on a spreadsheet or other paper-based methods for inventory control and management. These processes, either a spreadsheet or a manual one, both can cause common inventory management mistakes like:

  • Data entry error: Manual data entry invites lots of errors and results in misleading information.
  • Mismanagement in the warehouse: Well, we can say that data entry method is not the sole reason behind the error, but it is the type of data being recorded which disturbs the whole process. Since the entire process is manual, there is no mechanism available to check the data quality.
  • Poor Communication: Poor communication is the third setback within the organization, particularly between office administrative/executives and warehouse staff. This miscommunication often leads to error in data entry.

To avoid these mistakes, companies have started using computerized maintenance management software. The software can collect and process the IoT data to facilitate companies with perceptibility into inventory levels. Use of IoT data to foretell the inventory levels say stock-in and stock-out of spare parts in different locations, organizations can optimize the spare parts stock and control the expenditure on new expenses. For instance, you can schedule a visit whenever required and order the new stock as per the need.

Performance Measurement:

IoT data helps in making decisions related to asset and team performance. It allows the management team to monitor and track teams and assets to set Key Performance Indicators and track process (KPIs).

For example, you can find out the best performer in the team; in fact, calculate the team members’ regular average performance. Using the data, organizations can plan training and skill development programs for field service technician staggering. An organization can even organize reward, recognition and compensation program for star performers. In the same way, organizations can use data to replace the asset that is regularly causing threat and reducing downtime.

End words:

As we already know, IoT provides a lot more than we know, so using it for maintenance management functions can be a bliss for organizations. An organization should opt for better planning at the initial stage to ensure better data. Using relevant data, you can achieve reliable information and get enhanced decision-making capabilities. It is noted that early implementers of IoT in maintenance enjoy extraordinary benefits of transparency, visibility and efficiency in the operations. You should also review your on-going process and check how IoT can enhance your present maintenance management function.