The Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics. AI can be used to transform IoT data into useful information for improved decision making processes, thus creating a foundation for newer technology such as IoT Data as a Service (IoTDaaS).
AIoT is transformational and mutually beneficial for both types of technology as AI adds value to IoT through machine learning capabilities and IoT adds value to AI through connectivity, signaling and data exchange. As IoT networks spread throughout major industries, there will be an increasingly large amount of human-oriented and machine-generated unstructured data. AIoT can provide support for data analytics solutions that can create value out of this IoT-generated data.
With AIoT, AI is embedded into infrastructure components, such as programs, chipsets and edge computing, all interconnected with IoT networks. APIs are then used to extend interoperability between components at the device level, software level and platform level. These units will focus primarily on optimizing system and network operations as well as extracting value from data.
While the concept of AIoT is still relatively new, many possibilities exist to improve industry verticals, such as enterprise, industrial and consumer product and service sectors, and will continue to arise with its growth. AIoT could be a viable solution to solve existing operational problems, such as the expense associated with effective human capital management (HCM) or the complexity of supply chains and delivery models.
Applications of AIoT
Many AIoT applications are currently retail product oriented and often focus on the implementation of cognitive computing in consumer appliances. For example, smart home technology would be considered a part of AIoT as smart appliances learn through human interaction and response.
In terms of data analytics, AIoT technology combines machine learning with IoT networks and systems in order to create data "learning machines." This can then be applied to enterprise and industrial data use cases to harness IoT data, such as at the edge of networks, to automate tasks in a connected workplace. Real time data is a key value of all AIoT use cases and solutions.
In one specific use case example, AIoT solutions could also be integrated with social media and human resources-related platforms to create an AI Decision as a Service function for HR professionals.