The Artificial Intelligence of Things, an amalgamation of AI and IoT, is gaining much traction as businesses turn to digitalization. As the capabilities of these technologies are still evolving, they are now being leveraged across every industry where information and problem-solving can bolster outcomes for all stakeholders. AI and IoT are two distinct areas, but recent evolutions in connected systems have led organizations to integrate both technologies as a single unified one. Now, the convergence of AI and IoT is poised to bring industrial revolution and set to redefine the future of Industry 4.0.
AIoT is effective in assisting manufacturers to accomplish more efficient IoT operations and good human-device interaction, and enhance the capabilities of data processing. AI can be utilized to convert IoT data into meaningful insights for improved decision-making processes. This will help create a foundation for newer technology such as IoT Data as a Service.
The integration of AI and IoT is transformational and mutually advantageous for both types of technology. While AI drives value to IoT through machine learning capabilities, IoT adds value to AI through connectivity, signaling and data exchange. If manufacturers implement it properly, AI analytics has the potential to transform the IoT data into actionable information so that better decisions can be made.
As AIoT is very beneficial and valuable to industrial environments, it is significant to mull over the evolution of connected systems. The amalgamation of IoT devices has delivered companies greater control and visibility over key IT assets. For instance, outfitting production equipment with cloud-enabled IoT sensors gives the ability to manufacturers to optimize their workflows, minimize downtime and use predictive maintenance strategies. Cloud infrastructure has three components systems-connectivity, storage and compute. The technology allows a large number of devices to be seamlessly connected with each other with a continuing architecture.
Undeniably, AI is an unparalleled disruptive tech, and is predicted to have powered 40 percent of all digital transformation in 2019. Considering a report, the technology is estimated to reach from US$21.46 billion in 2018 to US$190.61 billion, at a growing CAGR of 36.62 percent. The growth of AIoT in Industry 4.0 also increasing as a majority of industrial sectors rely on operational technologies to manage operations such as manufacturing, supply chain, energy, and human resources, among others. So, integrating the developments of AI with IoT can unlock the new potential of precision and efficiency in manufacturing operations.
By combining AIoT into operational processes, manufacturers can attain greater levels of automation than ever before. This means AIoT intends to streamline the operation of connected systems, improve human-machine interfaces and supercharge data management and analysis. In other words, it allows automated systems to take counteractive actions when issues are detected, without any human intervention.
While AIoT is able to assess telemetry data from a huge number of connected devices in real-time, there are some fundamental issues to be ironed out in this tech. Those issues are mostly on the software side, both in the operating system and the application code, and the proper resource allocation and segmentation. Despite this, AIoT architectures are vital in industrial settings capable of envisaging equipment failures and shutting down damaged machinery before an accident occurs, eventually driving industry 4.0 innovations in years to come.