Data Analytics

Data and Automation Assist with Sustainability
admin
September 25, 2024
Data Analytics

How Can Data and Automation Assist with Sustainability in Your Business

The entire world is facing the inevitable digital transformation, which has not just changed the daily lives of ordinary men but has also changed the overall look of business operations in different industries. Technological progress and the introduction of innovative technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and automation are supporting company leaders to operate at better efficiency than ever before. They are capable of generating more revenue and delivering better services without any compromise. Hence making the globe a better place in the process. But the question is-How?

Why is sustainability a better method?

For many years, organizations of all sizes have acknowledged the intrinsic value of social, environmental, and governance (ESG) ambitions regarding customer retention and seamless operation at every step. Sustainability plans are smart business steps that can support company longevity and keep customers returning.

However, many company leaders acknowledge the importance of sustainable initiatives, but only one-fourth have embraced sustainability as part of their business model, as per the International Institute for Management Development (IMD).

To get the most excellent prospect for long-term business success, the Switzerland-based company stimulates executives and company policymakers to follow local laws and rules and take a more proactive direction to sustainability.

Data and automation technologies support by offering tools to established companies and startups to meet their sustainability goals.

Smashing barriers and executing green initiatives:

Ideally, an organization’s sustainable ambitions should be genuine and environmentally oriented instead of being focused on making profits.

Today’s tech-familiar consumers are using their spending power to support environmentally aware companies and are even willing to invest a few extra bucks in sustainable products and brands.

Future-focused companies maintain transparency by revealing their sustainability goals and ambitions and promoting customer feedback.

However, feedback would only be so effective if it has the capability to churn some sense from it, and automation can become a complete game-changer in this matter.

Automation software can support this by reducing data interpretation burdens, allowing companies to accelerate their green initiatives and save money along with time.

For instance, by using automation software, companies can swiftly and easily track energy use, the amount of waste produced each day, consumer habits, carbon footprint, and many other things in order to streamline operations. Based on the amount of data collected, it could take months for humans worker to organize and analyze the relevant information properly. Technology makes things much faster with greater accuracy.

Data-powered insights to disclose optimization:

When we talk about a company’s sustainability goals, waste minimization must be at the forefront of the conversation. For a valid reason-It’s challenging to know the exact numbers in industrial waste production. Waste generation is a significant global problem and is expected to grow with time.

In addition, solid waste management is indeed a wasteful process in its own way, causing approx 1.6 billion tons of greenhouse gas emissions into the atmosphere in 2016 alone, as per data shared by the World Bank.

Manufacturing may profit from the data-automation-sustainability interplay in a massively wasteful industry, beginning with conservative inventory management. Extra inventory can block the supply chain and landfills. Nevertheless, using data-based insights and intelligent automation, businesses can thrive in the balance between large and less stock, greatly reducing waste, emissions, and overall environmental impact.

Improved efficiency of operations:

Waste arrives in different ways, and many businesses are guilty of wasting time. The saying “time is money” gets into the process here-ineffective and inefficient operations and redundancies can heavily disrupt the day-to-day processes while wasting time and money of the company.

The good part is that automation can bridge some gaps, boosting the efficiency of processes at each and every level of the supply chain.

Human error leads to inefficiency and wastes the time and money of the company, and now company owners across industries are noticing this. Companies can now reduce workplace stress and monotonies through workflow automation. It allows employees to concentrate on meaningful work that boosts efficiency and makes fewer errors.

Companies ready to embrace and enforce workflow automation into their sustainability program should start small and know the operations wherein automation will provide them with the best result. The adoption will help achieve financial goals, environmental goals, or another plan altogether.

Measuring Weighing cost vs. benefit:

For small business owners, executing sustainability initiatives may appear more like a pipe dream than an achievable goal, as the technology implementation is costly. However, businesses that have already adopted technology to drive sustainability must hire skilled employees who can potentially use these resources and streamline operations for enhanced economic and environmental benefit.

As companies can utilize automation and data analytics to improve efficiency, alter energy use, reduce waste and otherwise support using sustainability, the expense of financing in automation is worth it. By empowering company leaders to see the big and better picture regarding carbon footprint, data and automation can support optimizing operations and enhance a company’s bottom line.

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Big Data is Changing the Outlook of the Renewable Energy Sector
admin
September 5, 2024
Big Data

How Big Data is Changing the Outlook of the Renewable Energy Sector?

The renewable energy sector is facing a significant transformation, and all credit goes to the power of big data. With its capability to gather, store, and analyze an immense amount of data in real-time, big data provides unprecedented insights into how we generate and use energy.

This has allowed companies in the renewable energy sector to create innovative solutions supporting us to adopt and create a more sustainable future.

So, let’s check how big data transforms the renewable energy sector and how the sustainable future will look!

Big data is a term used to describe the immense amount of data that organizations accumulate and analyze to achieve better insights into their operations. It can be sourced from various sections like:

  • Customer feedback
  • Transactional records
  • Sensor readings
  • Social media posts
  • Search queries, etc

All these together form a data set that can be utilized to make the most suitable decisions on the basis of analysis of correlations, ongoing patterns, and trends.

We can simply say that big data is a way to convert raw data into actionable insights, and this is what makes it so powerful.

Let’s know how big data functions

As we have already discussed, big data is utilized to collect and analyze vast amounts of data in real-time. This enables companies to understand consumer activities and behavior while optimizing their processes as well as operations.

Also, the analysis of big data can assist in identifying patterns that are unintentionally ignored. This is how companies are able to discover new opportunities and develop strategies accordingly. Not just this, big data also empowers organizations to get a better insight into their operations. 

For instance, energy companies can keep track of energy usage and identify areas where improvement is needed and efficiency can be enhanced.

Here, we can place the example of Tesla powerwall. It collects data from its solar panels to observe the production and consumption of electricity in real-time. Tesla’s power wall can be utilized to optimize energy usage by offering customers with customized options.

Three ways through which big data is transforming the renewable energy sector

So, at least, we have some knowledge of big data. Now, let’s find out how it is changing the renewable energy sector.

1. Improved Efficiency:

Big data analysis can support companies by identifying areas where efficiency can be enhanced in energy systems. For example, it helps in reducing wastage and optimizing output. This will ultimately improve the entire profitability produced by renewable energy businesses. This supports both seller and buyer as they can save energy costs and use the same to invest in other green-based projects or initiatives.

The skyrocketing cost of traditional energy sources has unveiled the importance of renewable energy. It has made it more attractive, and the involvement of big data can aid in making it more efficient. Big data will not only make renewable energy more feasible but will also make it a more attractive alternative for buyers.

2. Presaging Demand and Supply:

Big data can also be utilized to foretell the demand and supply of renewable energy.

By analyzing historical data, businesses can understand the market pattern and behavior and can easily calculate the present demand for distinct types of renewable energy resources. Therefore, they can change, shift, or adjust their production as per the need. In this way, companies can target a specific customer base, leading to more conversions and ultimately adding more profits. On the other hand, customers will also get whatever they want, so it turns out to be a win-win situation for everyone involved.

Other than predicting demand and supply, big data are also used to forecast weather conditions, which will allow businesses to plan their production of renewable energy resources.

For instance, the Tesla power wall can forewarn the weather conditions and shift energy production consequently.

3. Automation of a few processes:

In the end, we can say that the most significant advantage of having big data in the renewable energy sector is automation. By automating specific processes, organizations can save time as well as resources while making their operations more efficient.

For instance, solar panel systems can be linked to the internet and designed to adjust their output depending on weather conditions on a real-time basis. In this way, consumers can cut down their electricity bills by generating more energy when the sun is shining bright in the sky.

Besides this, companies can also utilize big data to automate the maintenance of their assets involved in renewable energy systems. By tracking and analyzing real-time data, they can interpret any issues and take action before they turn out to be a significant problem in the process.

Conclusion

With rising global temperatures and increasing greenhouse gases in the environment, it has become necessary to bend toward renewable resources for energy generation. The shortage of non-renewable resources and by-products it offers, like pollution, greenhouse gases, etc, is another reason to shift toward renewable energy resources.

In this initiation, the addition of big data is causing an immense impact on the renewable energy sector. It is making renewable energy more efficient by predicting demand and supply and automating a few processes to reduce time and cost. With the advancement of technology, in the coming years, big data will become an integral part of the renewable energy sector and churn the best result while promising a green and sustainable future.

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Big Data be Integrated into Your Business to Improve Output
admin
August 28, 2024
Big Data

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.

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Industrial Data Help Overcome All Business Challenges
admin
August 22, 2024
Data Analytics

How Can Industrial Data Help Overcome All Business Challenges

Today, if we see the ongoing competition between industrial companies, we can easily underline the challenging hurdles they face to become the best, primarily in operational objectives and in understanding the immense amount of data available to them to decide how best they are achieving those goals.

To meet this objective, industrial data management strategies must be adopted to leverage existing assets and systems to unlock the full potential of their plants and drive their businesses forward.

Currently, the flooding industrial data is mostly wasted. In fact, as per the European Commission, 80% of industrial data gathered is never utilized. Asset-intensive organizations need a holistic and integrated solution that offers seamless connectivity across all data sources while providing real-time monitoring capacity to ensure no data is wasted.

With such a broad framework, these companies can maintain asset reliability through predictive equipment failure analysis, reducing maintenance costs and improving overall plant efficiency. Yielding on this vision is a big task today as a flooding amount of data is present. Companies across these sectors have recorded and captured large amounts of data for decades. These data have incredible potential, and using them to good use is far easier than expected.

Unclosing high-potential value use cases that utilize this data in production optimization, machine learning, or emissions tracking needs potent data management strategies. After all, industrial data and systems have traditionally been located in organizational silos, having different pockets of functionality developed by various dealers at different times. This has made data management more difficult and rendered most data unusable at scale.

Going through the Data Lake confusion

To counter the challenges highlighted above, businesses often choose to construct data lakes in which data from different sources is collected.

These data lakes work as potential reservoirs that swiftly accumulate vast amounts of information.

Nonetheless, it is not easy to potentially utilize these data lakes as it requires a workforce skilled in data handling and analysis, ultimately creating a considerable challenge to industrial business. Hiring such highly skilled personnel becomes even more intimidating due to the promptly evolving workforce, where specialized expertise is at a compensation.

Going through this complex system requires a strategic approach, allowing businesses to unveil the full potential of their data lakes and secure a competitive benefit.

The need for real-time data platforms suitable for commercial use

An asset-intensive business offers potential solutions; however, traditional data historians remain key, allowing industrial organizations to access data, know what is relevant, place it into workflows, and make it usable. The market for these assets remains on an evolutionary path globally. As per Mordor Intelligence, it will grow from US$1.15 billion (€1.05 billion) in 2023 to US$1.64 billion (€1.49 billion) by the end of 2028, at a compound annual growth rate of 7.32% during the projection period. 

Today, plant operators and engineers use historians to monitor operations, analyze process efficiency, and look for new opportunities. These are target-oriented systems customized for the operation teams’ benefit. 

With time, there has been an increasing demand for cloud-based applications to aid advanced analytics and quickly scale up. Meanwhile, on the IT side, digitalization teams and products need to be structured, clean, and contextualized data to produce usable insights and expand use case volumes. 

However, different data sources, including historians, offer at-a-glance analyses; their customized nature makes it hard to automate consistency in contextualizing and structuring data.

Enforcing a new solution

The collaboration of plant-level historian solutions and enterprise data integration and management technology allows a uniform confluence of IT, that is, Information Technology, and OT, which is Operational Technology functions. Along with this, we are also noticing the rise of next-generation real-time data platforms, supporting industrial organizations in collecting, consolidating, cleansing, contextualizing, and analyzing data from their operations.

This data foundation shows the beginning point for the industrial organization to optimize processes using machine learning and AI and develop new working methods based on data-derived insights.

Such organizations will be competent in developing current data systems to gather, merge, store, and retrieve data to boost production operations with data-driven decisions or backing performance management and analytics across the business.

This new data consolidation strategy prints a key moment in the evolution of data management. An organization can unveil unimaginable efficiency, innovation, and visibility by centralizing information from different sources into a unified, cloud-based, or on-premises database. The collaboration of batch and event processing delivers track and trace capabilities and authorizes organizations to search into batch-to-batch analysis quickly.

Driving ahead positively

Today, industrial companies face umptieth challenges, including meeting operational objectives, comprehending large amounts of data, and improving asset reliability.

They need a data management approach that uses legacy assets and systems to manage these issues. This approach should have an integrated solution that enables organizations to connect all data sources, access real-time monitoring, boost asset dependability, and increase overall plant efficacy.

Conventional data historians are still crucial to this strategy but must be integrated with cloud-based applications, enterprise data integration, and management technology. This will help companies gather, consolidate, cleanse, contextualize, and analyze data from their operations. This real-time data platform has grabbed a competent place worldwide as companies seek solutions to enhance their operational efficiency and decision-making capacity. Not just this, companies will also be able to update current data systems to gather, store, merge, and get back the lost data. This will ultimately improve production operations with data-based decisions and help in performance management and analytics across the system.

Along with this, companies will also get access to real-time asset performance, track material progress through complicated processes, and interlink people, data, and workflows to support compliance.

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How to Address Data Management Challenges in IoT Using Fabrics
admin
August 7, 2023
Data Security, IoT

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.

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How IoT Data Analytics Impact your business
admin
April 3, 2023
Data Analytics, IoT

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.

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admin
February 23, 2023
IoT, Technology

What is the Impact of IoT on Global Logistics Development

We all know that today, the logistics market is dynamic and has become competitive. In the last few decades, logistics has been redesigned not just because of rising competition and circumstances in the world but also because the Internet of Things (IoT) has dived deeper into the logistics niche.

As per KPMG reports, market challenges are compelling participants to find new development points for the business and recreate existing supply chains, like rail transit in the Asia-Europe direction. A high empty mileage decreases the efficiency of cargo transportation and causes congestion on the decided routes. Let’s look at modern IoT logistics solutions; and how they impact international logistics and transport.

What is IoT in logistics?

We can simply understand this technology through examples such as IoT, a modern smart refrigerator door that orders the delivery of your favorite pizza and drinks, or a smart kettle that brews your coffee in one click from a smartphone. There are smart sensors in agricultural fields and drones with high-pixel cameras that allows farmers to monitor the condition of the soil. The world will become an entire Internet of Things complex in a few more years. 

However, when we mention the word Internet of Things, the first relation of this smart and emerging technology links with smart devices and tools that are physically available. Yet, IoT goes far beyond this and especially in global logistics.

IoT Logistics Examples

With the reduced cost of technology, the size of IoT devices also decreases. It is now quite apparent that devices and instruments are getting smaller with the growing market. Smaller sensors gather a more significant amount of data through creative and non-destructive placement.

Let’s assess what modern developments have been designed for us besides the sensors.

Warehouse & Inventory Management using IoT

IoT sensors track inventory and furnish data that can be utilized in trend analysis to presage inventory needs. Goods are automatically repositioned with stacker cranes’ assistance, production time and labor costs are cut down, and the human factor is balanced because the robot does not need leisure hours. This will bypass under-stock and over-stock situations.

Tracking Goods From Purchase To Delivery

Traditional monitoring depends on scanning an order between points of delivery. Special tags like RFID or Radio Frequency Identification simplify the search operation by connecting to the cloud and sending location data more frequently than scanning. This might get you back to the QR codes or Data Matrix times. Yes, they can also be used by analogy, but unlike FID, optical codes have to be scanned individually for each item, which takes time.

RFID tags reduce unnecessary expenditure. On average, the precision of inventory levels is approximately 65 percent. Employing RFID raises it to 95 percent. BigData monitoring under RFID will identify the most persuasive couriers and truckers, choose the most efficient delivery routes, and more. If delivery staff show unexpected results, they are sent for further revisions.

Drone Delivery

Drones are remotely controlled and unmanned aerial vehicles and droids that can improve the speed and efficiency of various logistics infrastructures. It is no more a trend or novelty as today’s developments are improving the accuracy and speed of their movement. As per the CompTIA poll, drones are employed by companies of different sectors and sizes. They enable the automation of business processes and allow smart inventory tracking, fast product transportation, and prompt delivery from stores.

Future Insights of IoT in Logistics

The proliferation of the Internet of Things in the international logistics market generated $34,504.8 million in 2019. Prescient Strategic intelligence shows a steady CAGR of 13.2 percent by the end of 2030. Nowadays, crucial assignments of logistics companies are the following:

  • Assure just-in-time delivery.
  • Offer transparency in the supply chain.
  • Ensure the transparency of the transport cycle and grade of services.

The success of any logistics company depends on effective stock and warehousing management, automation of internal business processes, prompt delivery, and assuring the safe storage of goods. Data becomes helpful when it passes through this cycle. Wireless networks like Bluetooth, GSM, Wi-Fi, etc., offer information exchange in logistics processes.

IoT has now become part of all the sectors where transport is involved. That is, its impact and usage are just not limited to logistics and transport. Instead, it is used in manufacturing and retail trade, including e-commerce, hospitals, construction, and many other sectors. This enables transparency of processes in the supply chain, better and more stable work of transport and employees, and saves company resources.

The logistics business is attaining a new height after embracing IoT, as it provides efficacious solutions aimed at working with Big Data, speeding logistics supply chains, and many other things. This is supported by other advanced trends like the proliferation of the 5G Internet, the fast growth of mobile applications, and cloud services.

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How IoT supports Electric Vehicle Charging and Keeps EVs Running
admin
January 3, 2023
IoT

How IoT supports Electric Vehicle Charging and Keeps EVs Running

The evolution in the vehicle industry is remarkable. The increasing vehicle demand is not just consuming natural crude oil but also giving pollution as its by-product. The increasing temperature of the earth is significantly impacting the lives of humans as well as animals. This menace is not just limited to living organisms but also disturbs the climate and ecology. 

With the emerging need to control the increasing pollution and make a drive more comfortable and safe, the addition of electronic vehicles is applaudable. Today, Electronic vehicles that are EVs have taken an ambitious place in many car manufacturing companies, proudly joined by Tesla, which is launching all-electric models. Electronic Vehicles are the need of the hour. 

With this remarkable evolution and acceptance by the crowd, there is an inevitable demand to have a solution to keep these cars charged outside of a home. 

Besides supplying the electricity to charge an electronic vehicle, electric vehicle charging stations provide a wealth of information to owners, operators, and drivers. The credit for these things goes to the Internet of Things and cellular connectivity.

Electric cars parking and charging lot.
Electric cars parking and charging lot

The futuristic IoT Charging Stations: Charging EVs

An Electronic Vehicle charging station is connected to IoT and offers numerous benefits to the operator and consumer. If we take up the consumer’s perspective, there is a lot of information and knowledge one needs to acquire, like the location of the charging stations installed on the way. How much time will it take to get the EV charged fully? How much will it cost? These are sets of questions that EV charging stations can answer. And often, these stations have facilities to pay directly from a mobile app because of IoT, making things convenient for EV owners. 

And if we take the operator’s side, IoT enables operators to achieve critical information about each EV charging station without physically visiting the station. It informs the operator about how often it is being used to alert for the upcoming maintenance required or failure of the machine. All of this information can improve efficiency, which, ultimately, helps in improving ROI. It helps in scheduling preventative maintenance or decreasing on-site time with the devices.

However, we are still living in the initial days of EVs, and we anticipate improvement in adoption and innovation with the government’s recent push to spend on climate change initiatives. 

Inflation Reduction Act: Funding in Climate Change

The Inflation Reduction Act has become a topic for discussion this summer. This broad proposition was created to encounter inflation, bargain prescription drug prices, and extend the developed Affordable Care Act program for three years. It invests in manufacturing, domestic energy production, and lowering carbon emissions.

The Energy Security and Climate Change Investments in the Inflation Reduction Act aimed to control energy usage, and positioned the U.S. on the route to minimize carbon emissions approx 40 percent by the end of 2030. This bill targeting the reduction in carbon emissions holds many vital aspects, including reducing energy costs for citizens, increasing energy security, attracting more investment for decarbonizing all sectors of the economy, funding disadvantaged or remote communities, and supporting resilient rural communities.

Inflation Reduction Act: Helping EV Growth

Compared to vehicles that run on natural gas or diesel/petrol, Electronic vehicle causes less environmental impact. It has been proven to be a better option that not just solves the traveling issue but also helps in saving the environment.

Everyone in the industry, either its manufacturers who build EVs or the consumers who enjoy the drive, can leverage the benefit. The benefit offered by Electronic Vehicle also includes:

  • Up to$10 a billion investment tax credit to develop clean technology manufacturing facilities, including those companies that manufacture electric vehicles, wind turbines, and solar panels.
  • Almost $2 billion in assistance to retool existing auto manufacturing structures to manufacture clean vehicles.
  • Up to $20 billion in loans to construct new clean vehicle manufacturing buildings across the country.
  • Govt is providing tax credits and assistance for clean fuels and commercial vehicles to decrease emissions from all parts of the transportation sector.
  • Almost $1 billion for promoting clean heavy-duty vehicles.

The Inevitable Demand for Connectivity

The development of IoT and its endless potential has changed the outlook of the entire world. From smart towns to smart streets, smart hospitals to smart homes, smart tv to smart bottles, IoT has leveled up the world and improved efficiency. The addition of IoT in almost all sectors, including electronic vehicles, has changed the working process while improving user experience.

The collaboration of IoT with Electronic Vehicles also marks that IoT holds the potential to save the environment and ecology; we just need to work more on this technology and exploit it to its full potential. In the coming year, we can expect more innovative solutions that will improve the service quality and also promise to stay environmentally friendly.

However, the introduction of electronic vehicles and the addition of IoT will indeed require more investment and evolvement. There are some challenges that need to be addressed. The extensive spending on clean vehicles will also drive the need for more connected charging stations across the country to support consumers, operators, and commercial vehicles. Electric vehicle charging stations driven by IoT will shortly become essential and significant support for all EVs.

Nevertheless, EVs will be the lifeline of the future transportation system, and IoT, along with other technologies like Artificial Intelligence and Cloud, will become its spinal cord. 

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Need Enterprise IoT Solutions for Digital Transformation
admin
December 20, 2022
Digital Transformation, IoT

Why do We Need Enterprise IoT Solutions for Digital Transformation?

We all are well aware of the changes brought by digital transformation, or we can say that digital transformation has achieved many advancements in the past few years. However, the primary question remains: Why do we need Digital transformation? The answer is that to stay competitive, businesses must adopt digitalization. It is mandatory to maintain the minimal digital standard. So, the question should be changed to What are the benefits offered by digitalization to the company?

Let’s assume that company is already leveraging the benefits offered by digitalization. But not everyone can implement or execute it seamlessly, especially considering the highly structured nature and operations in the difficult-to-reach area, increased safety requirements, and a small room for risk.

These challenges are commonplace in sectors like construction, agriculture, and mining. Luckily, the technologies backing digitalization are regularly upgrading to provide the most suitable combination of digital solutions for successful digital transformation. Let’s know how companies can start or continue digitalization using enterprise IoT solutions without the hassle.

Why go Digital?

Digital transformation has not been limited to desktop computers. The level of digitalization in a company can be estimated by the digitalization of its assets, usage, and labor. Product companies must enhance their products using digitalization, for example, by customizing thermometers or developing an agricultural product range with a digital irrigation system. 

According to recent statistics, almost 70% of companies embrace and have a digital transformation strategy or perform on it. These organizations represent the following reasons why digitalization can be advantageous for them:

  • Top Benefits of Adopting a Digital Model

Top Benefits of Adopting a Digital Model (Source: IoTForAll)

It is apparent that many of these factors are interdependent or outcomes of the same digital improvements. For example, by replacing the old-traditioned button-operated interface with the sensor interface in a tabletop printer, a company could boost its final product quality, which naturally impacted operational efficiency. Therefore, having a clear goal is vital for a potent digital strategy. A more thorough approach means a more valuable outcome. This is true for production and enterprise process improvement, as digital enterprise processes can enhance performance while IoT can speed up adoption.

Business IoT Solutions & Digital Transformation:

These four core target components give a holistic look at the digital enterprise of today:

  • Automation
  • Efficiency
  • Security
  • Maintenance

IoT-embracing companies are already familiar with the benefits and vital points of the IoT ecosystem development strategy. IoT adoption is considered one of a company’s digital indicators. However, it is more reasonable to consider IoT as a tool for enterprise organizations for transformation. This approach empowers to counter any inflated expectations, for instance, executing IoT components and expecting the company’s revenue to skyrocket. It is necessary to ensure that each tool is used appropriately and strategically.

Digital Strategies: 

An IoT implementation process is more intricate than various digital strategies. This is why we call it an IoT ecosystem, where all the components, from sensors to people, communicate with each other to achieve the primary business goals. Besides their extensive nature, IoT ecosystems are adaptable and permit companies to enforce them irrespective of their digital level.

Therefore, we suggest Enterprise IoT solutions for these two main digital strategies:

  • Initial digitalization: By creating an IoT ecosystem, businesses become digitized. By integrating crucial equipment, assets, vehicles, or cargo into intelligence, one can get real-time status, monitor environmental conditions, people’s activities, track location, etc. By adding analytical tools to the IoT ecosystem, one can predict equipment failure, create optimal routes or detect failure due to human factors. One can even add a cybersecurity program due to the potential vulnerability of the endpoints.
  • Advanced digitalization: Besides the capacity to deliver the vector for further business development, Enterprise IoT Solutions are best to estimate the other vector for the digital development of a company. For instance, if you execute a machine vision for improving QA processes at the first step, it is easy to track its efficiency and pick up complementary solutions. When all the essential assets are implanted with IoT sensors, companies can implement a digital twin and meticulously investigate data in their ecosystems. Therefore, you can get a solid analytical advantage empowering you to predict trends or simulate cases.

Enterprise IoT Challenges & Solutions

To know how to accelerate transformation, we must comprehend what slows down this process. Let’s know the major digital problems and solutions to overwhelming them.

1. Inventions Can Cause Disruptions:

Adding innovations brings a change in working models. This is true for highly structured sectors like mining, rail, and construction. Thus, they should regard digital solutions with structure in mind. The best benefit is that IoT technologies are flexible and can incrementally.

Now, we are familiar with successful cases of how some traditionally unsuccessful industries in digital have soared there in recent years. For example, in 2015, healthcare was one of the least digitized industries. But the story changed within three years, and in 2018, it became one of the top digital business strategy adopters, along with the financial and service sectors. Telemedicine, smart pharmacy, wearables, and smart hospitals have become part of the world; this shows that the healthcare sector is successfully managing the enterprise IoT adoption and will keep embracing it.

2. Lack of Safety:

If an enterprise IoT integration is technically challenging, the organization should spend more time on marketing research. The statistics are open, and enterprise IoT providers are updating their technical tools to outstretch the potential implementation area. In mining operations, which are usually held in vast and remote areas and have less connectivity, the best and most convenient solution is implementing mesh nets to ensure a reliable IoT ecosystem. As a result, one can monitor the entire area and get to know the health status of the machines.

3. Resistance:

Line workers are less resistant to innovation. Top management is typically the most resistant as they are responsible for the business. It is the only right decision to approach innovations efficiently by calculating all pros and cons. 

Therefore, higher-level leaders should get precise reports on how particular Enterprise IoT solutions will impact the business processes and revenue of the company. While making an execution strategy, it is essential to calculate all the situations, risks, and ROI and intercommunicate accurate statistics. Thus, there is a high possibility that a technology important for a specific enterprise will be backed.

IoT Ecosystem for Business Goals

Taking the IoT ecosystem not as an end goal but as an effective instrument to achieve business goals using digital transformation is more beneficial. Organizations’ main objectives are improving operational efficiency, meeting customer expectations, and enhancing new product quality. By enforcing enterprise IoT solutions, it is easy to get real-time insights. Enterprise IoT solution is compatible with initial and advanced digitalization as they can analyze large volume of data.

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How IoT Boosts the Micro Mobility Market
admin
December 8, 2022
IoT

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.

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