IoT And IoT Analytics

Internet of things (IoT) is well known and widely used technology nowadays. According to the definition of IoT, it refers to anything that can be connected to the internet in any form or that is part of a network of linked devices that gather and share data via embedded sensors.

Today we all are surrounded by multiple IoT devices that we are using in real-life day-to-day. Below are some of the examples of IoT devices,

Smart Home Appliances
Refrigerators, AC, oven, adjusting the room temperature, washing machines, lights, and fans, etc.
Healthcare
Tracking the well-being of patients in a hospital, connecting individuals to doctors remotely, checking blood pressure, heart rate.
Wearables
Tracking day-to-day fitness activity using various kinds of wearables available nowadays in the market.
IoT is also widely used in agriculture, industries, and corporate offices.

Why IoT Analytics?

In general, IoT data is collected in real-time after a fixed interval of time which is massive. This data is of no use until or unless we can get some insights or valuable results from this data which helps to either solve our real-life problems or grow our business using that data. Analyzing the IoT data in real-time helps to solve these problems.

For Example, IoT-based smart wearables are used to track fitness activity during the workout, which collects data like HR, BP, SpO2 levels using sensors. Now, this data can be analyzed in real-time to generate warnings to the users during the workout if any unusual pattern is found in the collected data. This task can be achieved using IoT analytics.

How to deploy IoT Analytics?

IoT Analytics can be achieved in the following way,

First, create and train your machine learning model using past available data.
Deploy the trained machine learning model either on cloud or edge.
Collect data in real-time using IoT devices and sensors.
Send your collected data to the place where the ML model is deployed using any IoT protocol and then pass the data through the trained model to generate the results.

Some already available platforms help analyze the IoT data in real-time. Two of them are listed below,

ThingSpeak
ThingSpeak is a cloud-based IoT analytics tool for aggregating, visualizing, and analyzing live data streams. ThingSpeak allows you to send data from your devices, see live data in real-time, and issue warnings. It works on MATLAB programming.
AWS IoT Analytics
AWS IoT Analytics is a fully managed service that automatically operationalizes analysis and grows to accommodate petabytes of IoT data. You can use AWS IoT Analytics to analyze data from millions of devices and create quick, responsive IoT apps without managing hardware or infrastructure.