Collaborative IoT agent in dynamic environment

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In the commercial RFID industry, it is required to tune the antenna power and adjust antenna position to achieve the best reading performance and also it is the most difficult part of the tuning process due to the dynamic environment. Due to the commercial RFID frequency characteristics, there are a lot of environment factors contribute to the signal instability. The research objective includes creating an agent simulation environment and tunning assistant tool. The collaborative agent simulation environment can be perceived as an environment to help researcher or engineer to analyse potential tuning setting combinations in the real world and also explore the possibility of future self-tuning RFID agent. Additionally, there are only few agents modelling framework/modelling toolkit available online and most of them are based on the java coding. Thus, it is essential to build a .NET based agent simulation environment. The tunning assistant tool can be perceived as an environment factor analyser to collect as many as the environment data, in order to improve the framework tunning accuracy in the future. This paper covers literature review (theory background), design, implementation and analysis process of applying Morphogenetic, Insect Vision and BDI models into the software architecture of RFID agent simulation environment framework and environment analyser, as well as, illustrates the agent internal interaction mechanism, and thus allowing multiple agents to work collaboratively to achieve the same goal at least effort. The research and development process followed agile development methodology, which is most suitable model for the multiple sprint cycles, in order to solve the new challenges, issues generated by self-evolved prototypes. To facilitate the research, there were 3 experimental projects implemented, which includes RFID distance detector, .NET agent simulation framework and environment factor analyser.
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