With IoT data being generated in zettabytes today, enterprises need to leverage this data to perform various monitoring, reporting, and decision-making tasks. By combining the IT and OT data, IoT analytics helps extract actionable and meaningful insights to help improve the overall business value. Read on to find out how IoT analytics can help with important business insights.
With the internet and wireless technology reaching to billions now, IoT has become ubiquitous. It has reached our homes, the vehicles we drive and the city we live in. Hence, each of us is generating a very high volume of data with the Internet of Things. Cisco predicts that by the end of 2021, IoT will generate 847 zettabytes of data per year and this number will grow exponentially.
Considering the rapid growth of IoT and connected devices, there is a thriving need among organizations to make sense of this IoT data with IoT analytics to extract important business insights that can be used as a competitive advantage and informed decision-making. For example, visualizations, reports, and alerts generated with real-time IoT data of an ecommerce website can be directly used to provide better customer experience. According to the Grand View Research, the global IoT analytics market size is expected to reach USD 57.3 billion by 2025 at a CAGR of 29.7%. However, when it comes to analyzing IoT data, it has its own challenges. Analyst firm IoT Analytics projects global IoT connections will reach 30 billion by 2025, driven by cellular IoT, low power wide area (LPWA) networks and wireless local area networks (WLAN).The connected car market witnessed accelerated growth in 2021, and sales should return to trend in early 2022, according to analyst firm ABI Research, which expects to see 115 million global connected car shipments, and a market value of US$83 billion in 2025. Wood Mackenzie Power & Renewables estimates that over the period 2020-2025, the total number of smart meters deployed will rise from about one billion to nearly 1.3 billion.
IoT data come in huge volumes, are highly unstructured, and differ in terms of variety (text, image or videos). Moreover, while the operational technology relates to the data collected from temperature sensors, pressure sensors, tablets, smart manufacturing devices/tools, etc., the information technology relates to the data collected from enterprise systems, legacy systems, ERP, CRM, and finance systems. Looking at only the OT or IT data in silos will not provide the necessary results. The OT and IT data have to be combined to make sense. Unfortunately, traditional analytics tools and technologies are designed to look at only the IT data and do not work directly on this combined dataset.
Moreover, cleansing of OT data from the noise, corrupt, and false readings is one of the major challenges in the IoT environment. For example, in a smart home system, to know when to proactively replace sensor batteries at the customer’s place for better service, a vendor will require customer transaction data from the enterprise systems as well as sensor data like device status, metadata, etc. Securely managing the IoT data, before passing for dashboard generation is another challenge posed when carrying out IoT analytics.
For industrials, IoT analytics applications lead to improved product quality, production efficiency, and customer service. By using smart manufacturing equipment, organizations can better understand the manufacturing process and potential areas for increased efficiency.
The use of Internet of Things analytics in the healthcare field is leading to a more patient-centric and holistic approach to healthcare due to the insights it can provide. Wearables and apps used outside of the hospital are allowing healthcare providers to monitor patient metrics and vital signs remotely also, automatically be alerted even when patients are not physically presented near their healthcare providers.
Due to the importance of speed and efficiency to generate the revenue in supply chain, many of the IoT applications in this industry have to do with its ability to optimize processes. The IoT is used to identify the exact location of both products and raw materials. Organizations can track and predict how a product develops and moves through the supply chain. This analysis helps to identify opportune areas to increase efficiency.
Both providers and end users benefit when IoT analytics are applied to the energy industry. For energy providers, energy meters equipped with sensors allow them to monitor and control the electrical network between production plants and different distribution points. For end users, they can gain insights on the consumption of energy.
IoT analytics encompasses data collection from OT and IT data sources and subsequent storage, processing, integration, visualization, and analytics to generate useful and actionable business insights.
There are various use cases for which IoT analytics can be applied. For home security and automation, data collected from different smoke, temperature, humidity, alarm sensors, etc., can be combined with customer data to enhance customer lifestyle experience, provide proactive data-driven services and bring in more operational efficiencies through remote monitoring, visualization, and troubleshooting.
In a smart building area, energy utilization dashboards can aid in sensor control, identifying specific times to heat or cool rooms, finding air quality threats, and deploying predictive fixes and maintenance. A study by Texas Instruments indicates that in HVAC and lighting IoT solutions, energy use can be cut by 40% just by sensor control. The same study also indicates that thermal comfort improves human productivity by 3%, impacting the bottom line.
In the retail industry, video analytics on the data collected from IP cameras can be used to check the theft detection and sweet heartening, to monitor entries and exit, etc. Also, the data from temperature tags and humidity sensors in the retail store can be used for forecasting shelf space replenishment, perishables, etc. Data from digital shelves can be used for real-time price and discount offers to customers.
Thus, there is a huge opportunity and value to be unlocked from edge data in combination with enterprise data to mine valuable intelligence through IoT analytics.
eInfochips has expertise in providing edge analytics to help clients in a highly-scalable, reliable, and cost-efficient infrastructure with custom solutions for IoT and Cloud. To know more, get in touch with us.
