IoT Security
Article | July 5, 2023
5 years ago, when we forecasted that the IoT platforms market would have a 5-year compound annual growth rate (CAGR) of 35%, we wondered if our growth projection was unrealistically high.
5 years later, it has become apparent that the forecast was actually too low. The IoT Platforms market between 2015 and 2020 grew to be $800 million larger than we forecasted back in early 2016, resulting in a staggering 48% CAGR.
Comparing what we “knew” back in 2016 to what we know today provides some clues as to why the market exceeded expectations so much. 5 years ago, no one really knew what an IoT platform was, let alone how big the market would be, which business models would work, how architectures would evolve, and which companies/industries would adopt them. The only thing that was “known” was that the IoT platforms market was a billion dollar “blue ocean” opportunity ready to be captured by innovative companies.
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IoT Security
Article | July 17, 2023
Three out of four IoT projects are considered a failure, according to Cisco. This is troubling but even more so when Cisco also found 61 per cent of companies say they believe they’ve barely begun to scratch the surface of IoT can do for their business? Businesses believe in the long-term value offered by integrating IoT into their business plan, however, they lack the knowledge of what is required to ensure the success of such a complex project. By studying past failed projects, technology leaders can gain a better understanding of why they failed and what they can do differently when evaluating and undertaking new IoT initiatives.
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Security, IoT Security
Article | July 13, 2023
Discover the crucial role of big data capabilities in unlocking the potential of IoT for businesses. This article covers their synergy, challenges, and value in decision-making and revenue generation.
Contents
1 Why Big Data and IoT Matter for Businesses
2 Understanding Synergy of Big Data and IoT
2.1 How IoT generates Big Data
2.2 Challenges of Processing Big Data from IoT Devices
2.3 Importance of Big Data in IoT Applications
3 The Value of Big Data and IoT for Businesses
3.1 Improved Decision-making for Businesses
3.2 Generate New Revenue Streams
4 Final Thoughts
1. Why Big Data and IoT Matter for Businesses
The internet of things (IoT) is connecting all types of physical assets to the internet, from smart wearables that track wearer’s vitals to connected industrial units that can report any malfunctions automatically. Big data in IoT is a natural outcome with the growth of IoT devices, with an immense surge in the amount of data being generated.
There are currently over 13 billion connected IoT devices worldwide.
(Source – Techjury)
This data is extremely valuable to businesses as it can help streamline operations, predict trends, and diagnose device issues. Certain functions of IoT devices that are crucial for modern businesses, such as enabling predictive maintenance, depend on the analysis of the data generated every second. However, to maximize the ROI from their IoT ecosystem, businesses must first manage and process the vast amounts of unstructured data they produce. This is where big data capabilities come in.
2. Understanding Synergy of Big Data and IoT
Big data and the IoT are fundamentally different concepts, but are closely connected. Big data is a term that is used for a great amount of data that is characterized by volume, velocity, variety and veracity (or the ‘trustworthiness’ of data). The IoT is a term for physical devices or objects linked to the internet using an assortment of technologies. Understanding the synergy between these two technologies will be critical for businesses looking to leverage their full potential.
2.1 How IoT generates Big Data
IoT is one of the primary drivers of big data growth. The vast number of interconnected devices in the IoT ecosystem generates a massive amount of data every second. This data includes information on user behavior, device performance, and environmental conditions, among others.
The nature of this data makes it challenging to store, process, and analyze using traditional data management tools. This is where big data technologies such as Hadoop, Spark, and NoSQL databases come in, providing the ability to manage massive amounts of data in near-real-time, enabling critical applications of big data in IoT. For businesses, processing IoT data is synonymous with processing big data, due to the nature of the data generated by an IoT ecosystem.
2.2 Challenges of Processing Big Data from IoT Devices
IoT data processing is a complex and challenging task due to several reasons. Firstly, the sheer volume of data generated by these devices is enormous and is only increasing. This requires a robust infrastructure and specialized tools to store, manage, and analyze the data efficiently.
This data is also generally unstructured, heterogeneous, and complex, making it difficult to process using traditional data management and analysis techniques. Moreover, it is often noisy and may contain errors or outliers, which can impact the accuracy of data analysis. Businesses also face a challenge when securing such vast amounts of data. Since IoT devices collect sensitive information such as personal and financial data at scale, it is critical to ensure that data is encrypted, transmitted securely, and stored safely.
Additionally, IoT devices often operate in remote locations with limited connectivity, making it challenging to transmit data to the cloud for storage and analysis. As IoT devices continue to proliferate and generate increasingly large amounts of data, businesses must adopt big data technologies to gain actionable insights from this data.
2.3 Importance of Big Data in IoT Applications
There are several use cases of the IoT where processing large amounts of data is essential. It plays a critical role in IoT applications, providing businesses with valuable insights that can be used to optimize processes, reduce costs, and improve overall efficiency. By collecting and analyzing large amounts of data from IoT devices, businesses can gain a better understanding of customer behavior, machine performance, and other critical metrics.
For example, big data in IoT can be used to identify patterns in customer behavior, allowing businesses to tailor their marketing efforts and improve customer engagement. Additionally, IoT devices can be used to collect data on machine performance, allowing businesses to identify potential problems before they occur, minimize downtime, and optimize maintenance schedules. The value of big data in IoT applications lies in its ability to provide businesses with real-time insights that can be used to drive growth, reduce costs, and improve overall efficiency.
3. The Value of Big Data and IoT for Businesses
Businesses looking to integrate big data in IoT must first consider their data storage and analytics capabilities. By understanding the value of big data technology in capturing and analyzing IoT-generated data, businesses can unlock insights that can help them make better decisions, optimize processes, and create new business opportunities.
3.1 Improved Decision-making for Businesses
IoT and big data technologies offer businesses a wealth of data that can be used to make better-informed decisions. By integrating IoT sensors and devices with their operations, businesses can collect real-time data on customer behavior, operational performance, and market trends. This data can then be analyzed using big data analytics tools to generate valuable insights that can inform decision-making.
For example, operational data can be analyzed to identify inefficiencies and areas for optimization, helping businesses reduce costs and improve efficiency. With the right data storage and analytics capabilities, businesses can leverage the power of IoT and big data to gain a competitive advantage and make better-informed decisions that drive growth and success.
3.2 Generate New Revenue Streams
By leveraging the vast amount of data generated by IoT devices and analyzing it with big data analytics tools, businesses can gain insights into customer behavior, market trends, and operational performance. These insights can be used to create new revenue streams and business models, such as subscription-based services, pay-per-use models, and predictive maintenance services.
For example, IoT sensors can be used to collect data on equipment performance, allowing businesses to offer predictive maintenance services that help prevent equipment breakdowns and reduce downtime. Similarly, customer data can be analyzed to identify new revenue opportunities, such as personalized product recommendations and targeted advertising. With the right strategy and investment in IoT and big data technologies, businesses can unlock new revenue streams and create innovative business models that drive growth and success.
4. Final Thoughts
Big data in IoT is becoming increasingly important for businesses, and the future prospects are bright. As IoT continues to grow and generate more data, businesses that can effectively analyze it will gain a competitive advantage, leading to increased efficiency, reduced costs, and higher ROI. To fully realize the benefits of IoT, businesses must develop big data analytics and IoT devices in tandem, creating a feedback loop that drives continuous improvement and growth. By embracing these technologies, businesses can make data-driven decisions and unlock new insights that will help them thrive in the years ahead.
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Industrial IoT
Article | July 16, 2022
Every major industry, including retail, transportation, banking, healthcare, and energy, has significantly benefited from the Internet of Things. Processes like supply chains are where the Internet of Things best demonstrates its promise. Applications for management, forecasting, and oversight aid fleet managers in increasing distribution's operational effectiveness and decision-making openness.
Some of the primary goals for IoT deployment in supply chain management include tracking and monitoring. For example, warehouse and fleet managers can use technology to keep an eye on their stock and freight.
Reasons to Use IoT in Supply Chain Management
Real-time Location-tracking
Thanks to the Internet of Things, managers have access to a consistent stream of real-time data on the product's location and the environment surrounding transportation. You may keep track of the delivery of both finished items and raw materials, and you will be informed if the product is transported in the wrong direction.
Monitoring of Storage Conditions
Environmental sensors allow management to monitor cargo conditions and take immediate action when something changes. One of the most popular IoT supply chain systems, for example, collects data on pressure, humidity, the temperature inside vehicles, and other factors that could harm the goods and then automatically adjusts the environment.
Enhance Your Emergency Planning
Supply chain managers can design routes with the use of IoT and data analytics, taking into account traffic, weather, potential accidents, and other delay-causing events that may occur along the way. The Internet of Things collects all the data required to create adaptable backup plans and identify the source of any current delays. Also, supply chain managers can get alerts from the system in real time, which speeds up reducing risks.
Forecast Goods Arrival and Movement
IoT devices and data analytics systems are used by managers to enhance the decision-making process and boost the accuracy of delivery estimates. Real-time tracking lets businesses keep track of products as they are shipped, predict when they will arrive, and plan for and reduce the risk of delays.
Conclusion
There are many different IoT applications for supply chain management. For example, it improves communication between parties, makes it easier to track and monitor commodities, and makes planning more precise.
As long as you have a clear goal for what you need the technology to achieve for you, an IoT-based platform is an excellent investment for both small and large organizations. It's also essential to bring on a talented team for the design and development phase.
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