Analytics of things (AoT) is the next buzzword in the analytics industry after the popularity gained by Internet of Things (IoT).  AoT is the next step for organization implementing IoT. But first let’s understand what AoT and IoT actually mean and how are they interconnected.

Understanding Analytics of Things

Internet of things (IoT) for layman means that devices are connected to the Internet and they are transmitting data to a central repository.  While huge amount of data is being collected but mere data collection of little help to businesses. What they need is the analysis of data in order to make decision relevant to the business. This is where Analytics of Things comes into picture. Analytics of things conducts analytics on the data generated by IoT devices.

The name ‘Analytics of Things’ itself suggests that conducting analytics on things and in this case ‘things’ are nothing but IoT devices. So in simple words Analytics of Things is nothing but IoT analytics. It is the extension of an organization’s existing business analytics. That is why AoT seems like the next logical step to IoT. IoT alone will not make sense as without conducting analytics, mere data collection will be of little use.

Uses of AoT

AoT in the simplest form can be explained through a smart thermostat. These smart thermostats are made in a way that they can sense the temperature of the room, how many people are there in the room, pattern of people activity, etc. and adjust the temperature accordingly. Now, for a thermostat to do that is possible because it has been embedded with analytics and it is with the help of this analytics that it functions. The smart thermostat is collecting data and AoT helps to analyze this data and hence improve the functioning of thermostat.

AoT has various uses, some of them are highlighted here. AoT can be used for predictive asset maintenance i.e. through AoT, it can be understood the best time to service a particular machinery rather than servicing it at predetermined levels, hence improving efficiency.

Another example would be of using sensors to collect traffic data and then applying AoT on this data to determine where additional lanes are needed or how to optimize stoplight timing or any other way to manage traffic.

Why do we need AoT?

Analytics of IoT devices is needed to make IoT devices more efficient. In fact, IoT’s full potential cannot be realized without the use of AoT. AoT helps to understand the huge data that the IoT devices are generating and only by analyzing it, the data becomes useful, not by collection. Also AoT displays integrated information i.e. it pulls together all the information generated by IoT devices in one place so that it is easy to monitor and compare.

With the help of AoT, organizations can interpret and make sense of the data that is being generated and thereby can take necessary steps to improve the business as a whole and improve their bottom-line. Using AoT, organization can get answers to the challenges faced by them and find new innovative solutions.

Challenges faced by AoT

AoT is the need of the hour. However, IoT itself is still evolving and AoT is at a very nascent stage. Hence AoT faces a lot of challenges.

One of the major challenge is storing large amount of real-time data generated by IoT devices. The data generated by each sensor is humongous and storing & managing such huge amount of data is a big challenge. Also not all the data transmitted by IoT devices are meaningful and useful. So the challenge lies in how only the necessary data can be transmitted to avoid junk data thereby making its storage and analysis easier.

Another challenge faced is that of privacy of data. It is important that the data generated from devices especially at confidential places is secured and its privacy is maintained in order to protect the integrity of the overall system.

AoT success depends upon the standardization of the communication protocol between IoT devices. Hence standardizing the communication protocol is another big challenge faced by AoT.

What lies ahead?

A lot of challenges lie ahead of AoT for it to be successful. It’s only with time that these things will evolve and prove its worth. Organizations need to realize the importance and the potential of AoT in bringing success to their business. Organization generating huge data or expecting to generate huge data, need to start building up on their analytics capabilities and AoT is the way forward for such companies. It is important on the part of such organizations to invest in technology and skilled human resources for AoT to be successful.