The world population is at 8B according to United Nations. At present, more than 5B people have mobile phones and half of these connections are estimated to be smartphones. The smartphone penetration in a developed country such as USA is at 92% (statista, 2023) with over 310m smartphone users. In Brazil, a developing country, the smartphone penetration is at 79.72% and in India, it is at 54%. With this rise in smartphone and internet users across the world, Internet of Things (IoT) is also seeing massive growth.
‘The Internet of Things (IoT) is a network of devices that are connected to the internet and are capable of collecting and sharing data.’
The rise of smartphone connected IoT devices is unprecedented in last few years and currently we have 15B IoT devices which are only going to double by 2030 as per latest estimates. Internet of Things has truly become Internet of Everything with smartphones to smart lighting, smart speakers, voice assistants like Alexa, Google Home, smart kitchen appliances, connected vehicles etc.
This vast network of connected devices generate a great amount of data that can be either disregarded or analyzed for making data driven decisions. And this is where IoT analytics comes in play.
‘IoT analytics refers to the method of using data gathered from connected devices and networks to generate insights and make informed decisions.’
IoT analytics is becoming increasingly necessary due to the sheer volume of data generated by the numerous IoT devices. The data generated by IoT devices is typically unstructured and complex, making it difficult to analyze and understand manually (by humans).
Why IoT analytics is needed?
The growing need for IoT analytics has been driven by several factors and most important one being ‘providing insights into business operations and making data driven decision making’ mainstream.
IoT devices are becoming more prevalent in everyday life and can be found in homes, businesses, and even in entire cities, providing a wealth of data that can be used to improve efficiency and productivity.
The IoT technology is rapidly revolutionizing many business domains including retail, healthcare (IoMT), supply chain and manufacturing, oil and gas industries etc. Smart city and smart home development projects are also IoT driven with LPWAN (Low Power Wide Area Network) technologies such as LoRa, Sigfox, NB-IoT and LTE-M coming in.
The data, thus, generated by IoT devices can provide valuable insights into the behavior of customers, employees, and even machines (IIoT). Subsequently, this information can be leveraged to optimize business processes and improve decision-making.
The rise of artificial intelligence (AI) and machine learning has made it possible to analyze vast quantities of data quickly and accurately providing an opportunity to businesses to make better use of their IoT data and extract insights that were previously impossible to glean.
How IoT analytics work?
Various kinds of IoT devices such as wearables, sensors, and voice activated assistants collect all kinds of data. Wearables such as fitness trackers and health vital monitoring devices can collect data on your body weight, blood pressure, heart rate, blood glucose, sleep cycle, etc. and this data can be used to chart out workout routines and diet regimes for individuals. This is just one example here. So, what are the technologies that make it possible?
For IoT analytics, first step involves data collection and data cleaning. While the data collection is done using wireless networks and sensors, data cleaning is slight different. With the help of advanced AI tools the data is organized, data format is corrected and inconsistencies are removed. With the help of cloud computing, the data is then processed to generate patterns and insights that are easy to understand. Use of machine learning algorithm to forecast, based on past data, is the final step.
The Iot analytics is greatly important for businesses running huge operations where IoT devices collect massive amount of data. Analysis of such vast amount of data (say in retail business) will result in great inventory control, order fulfillment, analyzing customer behavior and forecasting demands and expectations pushing growth and value creation to new heights.
To conclude, IoT analytics is a critical tool for businesses and organizations that want to take advantage of the vast amount of data generated by IoT devices. By using IoT analytics, businesses can better understand their customers, optimize their operations, and make more informed decisions. As such, IoT analytics is likely to continue to grow in importance in the coming years.
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