Among other cutting-edge technologies like Blockchain and edge-computing, AI and IoT rest at the pinnacle of making disruptions in an industrial ecosystem. IoT and AI development companies, in collaboration with businesses, are now looking for new ways to find operational efficiencies in industrial setups.
On an individual level where these technologies in themselves are quite beneficial for industries, their amalgamation imparts even greater unprecedented advantages on a larger scale. Collectively, these technologies enable the development of connected intelligent machines that share information with each other and take well-informed decisions without any human intervention.
AI is currently a growing technology. By the end of this year, it is expected to reach a market valuation of $153 billion. Its adoption has the capability to boost the production rate and reduce labor costs by 30%.
IoT is also expanding ubiquitously. The connected devices are forecasted to cross the 80 billion benchmark and develop data of around 180 zettabytes by 2025. In order to manage this large volume of data and develop useful insight from them, AI in the near future can be expected to become an instrument with agile and high-performance solutions.
AI as a Challenge Terminator for IoT:
Other than security issues, the biggest challenge that IoT systems currently face is the ingestion and management of large amounts of data from end devices. In order to manage, analyze, and create useful insights from this data, the processing capabilities of Artificial Intelligence are now being explored.
Implementation of artificial intelligence makes devices and machines smart and intelligent on different levels:
1) Assisted Intelligence:
In this level, AI allows the identification of risks and give companies the ability to predict or forecast breakdown. They can monitor their machines in real-time, prevent downtime conditions and increase overall efficiency.
2) Augmented Intelligence:
In this level, AI offers machines the intelligence to take self-decisions and warn humans about the potential malfunctions or bottlenecks.
3) Autonomous Intelligence:
Machines gain the prowess of autonomy and can hence take necessary actions at this level of intelligence. They learn new ways to do things and hence contribute an effective role in boosting the production rate of the company.
Based on the level of intelligence they want to embed in their machines, industries can use AI (along with machine learning) to process the data transmitted from IoT devices or connected machines.
IoT and AI advantages in an Industry:
1) Complete Autonomous Environment:
Internet of Things allows enterprises to monitor their complete end-to-end operations and processes in full-depth. They can use the telematics capabilities to detect anomalies and get useful insights about daily procedures. However, data processing through traditional methods is quite conventional and time-consuming.
AI crunches data at a more rapid pace and allows enterprises to take necessary actions in real-time. This faster response helps companies to boost their production rate. Moreover, AI also creates an autonomous environment that allows machines and different pieces of equipment to interact with each other and perform necessary actions without human intervention.
2) Improved Overall Efficiency:
Data analytics and data mining are among the most invested field that companies explore to develop useful insights, patterns, and trends. IoT lowers the dependence of companies over data scientists and analysts by helping them create a continuous flow of data from their end devices.
Artificial Intelligence offers an advanced level of analytics to enterprises that they can use to evaluate the performance of their individual components. The AI-based data analytics is much more effective than the traditional systems and can hence be used to boost the overall efficiency of a facility and elevate the production rate.
3) Predictive Maintenance:
Artificial Intelligence makes machines or any other equipment smart enough to detect anomalies and monitor parameters that may result in unwanted malfunctions or bottlenecks. Companies can hence jump from scheduled or condition-based maintenance to preventive methods of conducting repairs and restorations.
Predictive maintenance lowers the possibility of sudden breakdowns and downtime that further helps enterprises to improve their efficiency. As per research by Deloitte, AI and IoT can:
• lower maintenance planning time by 20% to 50%.
• boost equipment availability and uptime by 10% to 20%.
• reduce maintenance costs by 5% to 10%.
4) Increased Scalability:
IoT devices can range from high-end computers to microsensors and chipsets. However, a standard IoT system includes the use of battery-powered sensors that contribute to the development of huge data volumes. Artificial Intelligence identifies and summarises the large inflow of data and scrutinizes the necessary information that is then passed to other devices and stored on a cloud platform. This helps the management of a big data flood at a convenient level and allow leveling up the scale of an IoT ecosystem.
Some Common Applications of IoT and AI Blend:
1) Robots:
Manufacturing is the biggest industrial adopter of quintessential technologies like AI and IoT. Robots are nowadays an important piece of equipment for a production firm. They are responsible for the movement of materials, fabrication, and machining tasks. With the embedment of sensors, robots are now becoming smart and self-dependent. Along with AI technology, these robots have now gained the ability to make informed decisions and work collaboratively to increase production in manufacturing units.
2) Self-driving cars:
Self-driving or semi-autonomous vehicles are the best examples of IoT and AI working together. They become a part of a connected network and operate based on different circumstances on roads. The vehicular AI systems can predict drivers’ behavior, identify pedestrians, determine road conditions, and monitor traffic congestions to control the driving of the vehicle.
3) Queue Detection:
Retailers often have to deal with long queues on checkout counters. AI uses different data points like cameras and sensors to detect the movements of customers and accordingly manage long queues. The AI system can also suggest dynamic staffing levels to maintain a continuous flow of customers, reduce checkout time, and increase the productivity of the cashiers.
4) Smart thermostats:
Smart thermostats are another good example of using AI and IoT powered systems. Users can use a smartphone to check and manage the temperature of a room from remote locations as per their personal preferences. The system can also be used to manage the temperature of a room based on the ambient conditions and number of people in the room.
CONCLUSION:
New products and services are being developed based on the fusion of AI and IoT technologies. Other technologies like Blockchain and edge computing are also becoming more prevalent and their amalgamation with IoT also offers new applications. The smart contract solution is one such application of the mixture of IoT and Blockchain. Soon these technologies will explode with new benefits that will facilitate the creation of a connected, smart, and intelligent world.
