Improving Wireless Sensor Networks Effectiveness with Artificial Intelligence
Piyush Raja, Santosh Kumar, Digvijay Singh, Taresh Singh · 2023
Although Artificial Intelligence's key goal is to create systems that mimic a person's intellectual and social ability, Distributed Artificial Intelligence follows similar objective then with an emphasis scheduled social principles. A concept of multi-agent networks is a new model designed for improvement of Distributed Artificial Intelligence. Multi-agent structures are composed of several interconnected intelligent systems called agents that can be deployed as software, a dedicated computer, or a robot. In a multi-agent environment, intelligent Agent exchange information with one another in order to coordinate their organisation, delegate assignments, and share information. Multi-agent systems, artificial societies, and simulated organizations are all part of a new computing paradigm that includes issues like cooperation and competition, coordination, collaboration, communication and language protocols, negotiation, consensus creation, conflict detection and resolution, and collective intelligence activities carried out by mediators (e.g. problem solving, preparation, knowledge, decision constructing in distributed method), cognitive multiple intellect actions, social then active constructing, distributed management and switch, security, consistency, and robustnes. Circulated intellectual sensor network may be situated viewed as a structure made up of numerous mediators (The sensor node), with sensors cooperating to form a collective system whose aim would be to collect data from physical sources variables of systems. Sensor networks may thus be viewed as multi-agent structures or artificially ordered communities that use sensors to sense their surroundings. However, how can Artificial Intelligence mechanisms be implemented inside WSNs? The dilemma can be approached in two ways: the first solution has programmers consider the overall goal to be achieved and develop together agents and multi-agent system's interaction process. In the second strategy, the author imagines and builds a group of self-interested agents, which then use evolutionary learning methods to adapt and communicate in a secure manner.