Internet of Things (IoT) represents the extension and evolution of the Internet, which has great potential and prospects for modern intelligent service and applications. However the current IoT is still based on traditional static architectures and models by our deep investigation. It lacks enough intelligence and cannot comply with the increasing application performance requirements. By integrating cognition into IoT, we present a new concept of Cognitive Internet of Things (CIoT) and its corresponding intelligent architecture.
Most of the current offerings from several point solution vendors for Internet of Things (IoT) focusses on how to connect devices to see, hear, smell the physical world around and report the observations. However, I would argue that only connectivity and reporting is not enough but capability to learn, think and understand both physical, social and contextual data and apply intelligence is the key. This requirement drives us to develop a new model called “Cognitive” Internet of Things. What is Cognitive? It is more appropriate to refer to “cognition” as an “integrative field” rather than a “discipline” since the study on “cognition” integrates many fields that are rooted in neuroscience, cognitive science, computer science, mathematics, physics, and engineering, etc.
Cognitive computing is one of the most exciting developments in software technology in the past few years. Conceptually, cognitive computing focuses on enabling software models that simulate the human thought process. More specifically, cognitive computing enables capabilities that simulate functions of the human brain such as voice, speech, and vision analysis. From this perspective, cognitive computing is becoming an essential element to enable the next wave of data intelligence for mobile and IoT solutions. Text, vision, and speech are common sources of data used by mobile and IoT solutions.
As per IEEE, Cognitive Internet of Things is a new network paradigm, where (physical/virtual) things or objects are interconnected and behave as agents, with minimum human intervention, the things interact with each other following a context-aware perception-action cycle, use the methodology of understanding-by-building to learn from both the physical environment and social networks, store the learned semantic and/or knowledge in kinds of databases, and adapt themselves to changes or uncertainties via resource-efficient decision-making mechanisms, with two primary objectives in mind:
- bridging the physical world (with objects, resources, etc) and the social world (with human demand, social behavior, etc), together with themselves to form an intelligent physical-cyber-social (iPCS) system;
- enabling smart resource allocation, automatic network operation, and intelligent service provisioning
The development of IoT depends on dynamic technical innovations in a number of fields, from wireless sensors to nanotechnology. Without comprehensive cognitive capability, IoT is just like an awkward stegosaurus: all muscle, no brains. To fulfill its potential and deal with growing challenges, we must take the cognitive capability into consideration and empower IoT with high-level intelligence.