IoT Data Analytics: Uses and Varieties
At this point, almost everyone seems to be at least familiar with the Internet of Things (IoT) concept. Now, as is the usual nature of technologies, i.e., they tend to evolve with time; IoT has grown since it first emerged on the scene, and, consequently, several subsets have come to the fore. One such subset that has generated quite a bit of interest across the globe is IoT data analytics. But what exactly is it? Let us find out.
What is Internet of Things Data Analytics?
The concept is quite simple — IoT data analytics is collecting, analyzing, and interpreting all the data generated by IoT devices. As you might know, IoT devices are connected to the internet, including anything from smart appliances and wearable fitness trackers to autonomous vehicles. So, what happens is that these devices generate a continuous stream of data, and IoT analytics is then brought in to help glean valuable insights from said data, thus driving informed decisions.
IoT Data Analytics: Types:-
● Descriptive Analytics: Herein, historical IoT data is analyzed to understand past events by summarizing historical data trends and key performance indicators (KPIs).
● Diagnostic Analytics: This type focuses on the ‘why,’ using historical data to find the root cause of problems or specific occurrences.
● Predictive Analytics: Focusing on what is likely to happen, this type of analytics forecasts future events or outcomes based on historical data patterns and trends.
● Prescriptive Analytics: The idea behind this type of analytics is to recommend what to do next — so it recommends specific actions or strategies to help optimize outcomes.
IoT Data Analytics Applications:-
Now, let us also take a closer look at the different applications of IoT analytics.
● Improved healthcare: Wearable fitness trackers’ medical sensors gather real-time health data, which is then analyzed to help doctors monitor patients remotely, enabling timely interventions, reduced hospital readmissions, etc. Plus, predictive IoT analytics on healthcare data can help hospitals identify individuals at risk of specific medical conditions, thus allowing for quick and early intervention and personalized treatment plans to help improve patient outcomes. Hospitals can also use IoT data analytics to help optimize the allocation of resources across their facilities. This means managing bed occupancy, staff scheduling, equipment maintenance, etc. This, in turn, helps substantially improve the levels of efficiency across the facility as well as patient care quality.
● Smart cities: IoT analytics is being used and can be further used to improve smart cities in several ways. For example, IoT data analytics can be put to work to monitor traffic patterns and identify areas that tend to get congested. This information can then be used to reduce congestion and improve travel times for residents. Yet another aspect where this nifty tool can work in smart cities is ensuring energy efficiency. While smart meters and sensors monitor energy consumption, IoT analytics can help lower utility costs.
● Supply chain optimization: While IoT data analytics can be used in countless ways in supply chain management, one of its most important applications is inventory management. IoT analytics can help monitor inventory levels in real time and identify potential stockouts, eventually optimizing inventory levels.
To conclude, the development of IoT and big data is accelerating. It is affecting all technological and business sectors while increasing the benefits. IoT and extensive data development are accelerating as they affect all technical and business sectors. While increasing the benefits for both businesses and individuals, there’s an increasing volume of data created by IoT systems. It has played an essential role in the big data environment, promising to improve the capabilities of existing IoT systems. So, go on and start looking for a trusted service provider for IoT data analytics right away!
