Transforming Industries Through Artificial-Internet-of-Things

Transforming Industries Through Artificial-Internet-of-Things

Deploying AIoT in different industries will enable organizations to work efficiently.

The world is now revolving around technology. As the world is evolving, one can see the growing dependence of humans with technology. Especially in organizations and businesses where the transformation of infrastructure, services and business models is being viewed as an imperative decision for the long run. One such technology that has been amongst the front runner and the possible change-maker in the industrial set up is Internet-of-Things (IoT). Experts believe that IoT is the driving force that would redefine Industry 4.0. By integrating IoT, with artificial Intelligence, thus forming a culmination known as AIoT, the reformation amongst businesses will be redefined. A report by Gartner states that by the year 2022, more than 80% of the enterprises would deploy AI with IoT.

The AIoT provides a platform for the improved business model, enhanced efficiency, meet growing demand, and for instilling better customer experiences. While IoT is tagged as the spinal cord of all operations in AIoT, experts have identified AI to be the brain of IoT, thus controlling all operations.

How does AIoT work?

AIoT is a unique combination of Artificial Intelligence (AI) and the Internet of Things. The IoT has sensors data or telemetry data that is governed by cloud computing. The telemetry data is sent to the cloud, where the large datasets and insights are stored. Thus storage, connectivity and computing forms the foundation of IoT, and collecting a large amount of datasets, storing it in scalable storage systems, processing big data to provide insights, using this analysis for rich visualisations, and controlling the devices with the insights provided by the big data analysis are the capabilities of IoT. A report by Juniper Research states that the IoT connected devices would triple to almost 38 billion in 2020.

Integration of AI in IoT, adds another capability of acting and rectifying the loophole or gaps within the system. AI scrutinizes the patterns with the telemetry data, identifies the gaps that is hindering in the process of automation and then starts initiating action, thus self-healing in the process.

Thus unlike IoT which only reacts to the gap in a system, AIoT analyses the pattern of telemetry data, augments it and generates a solution that would detect the failures and self heal it.

Manufacturing with AIoT

A shift has been observed from traditional production model to the process of the digital manufacturing process, which supports fully automated plants. A report by World Economic Forum has identified that more than 1000 factories have ventured in the path of transformation with AIoT, which has been observed by experts, increases volume production, mass customization and ensures that profitable production can be generated for the efficient functioning of business models.

Sensors which are embedded in the factory devices such as remote sensors, and smart meters, collect the telemetry data. Installing these devices with AIot, facilitate in analysing the data and identifying the gap within the production model in factories and plants, and hence rectifying the problem, without depending upon the external source. Such an approach warrants quicker product delivery to the market, efficient production, and increase in business automation, improved business agility, and enhanced customer experience.

By analysing the telemetry data, insights can be drawn out about the customer services and experiences, about the gap that requires to be addressed and strategies that are needed to mend these gaps. Also, unlike the traditional production model, with the utilization of AIoT, the production staff gets information for decision support that must be delivered ensuring smart production.

Automobile Industry with AIoT

The hype of smart cars uses technologies such as IoT, where sensors are embedded for collecting data, storing it, and connecting it with the various devices. Augmenting this telemetry data with AIoT, assists in accessing the data, that not only renders the smart cars to identify the blockages, road patterns or internal issue but also to respond by self-controlling the operations of the car, maintaining the car speed and changing the direction of the car, as and when demanded. A report by Mckinsey Insight states that, by the year 2030, 15% of cars will be autonomous and would be utilizing technologies such as IoT.

Agriculture with AIoT

In agriculture, identifying the climate condition, monitoring crops and identifying pests are imperative for increased yield in production. With the help of AIoT, a formula will be deployed in the farming plants where the data will be collected, by monitoring crops to identify any pest damage or deficiency that is causing the crops to wilt and damage. If the collected data, implies any kind of damage to the crop, the formula can be tailored accordingly. With the use of AIoT, those formulas will be delivered that ensures high crop yields.

Healthcare with AIoT

Healthcare is already deploying robotics and artificial intelligence for ensuring that improved healthcare services are delivered to the patient. By integrating AIoT in surgical robots, the robots would not only able to identify the problems associated with surgery, but the AI would also enable them to analyse the telemetry data, and utilize it during delicate surgeries.

In other areas of healthcare as well, the AIoT would help in connecting different medical devices, assessing the patient health data and find the pattern of any disease, based on this.

Thus the use of AIoT in all the sectors are viewed to be revolutionised by AIoT. If strategically deployed, organizations can utilize AIoT for cost-effective and efficient operations.

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