Algorithms for radio transmission power control and data transmission reliability in wireless sensor network

Industrial automation is becoming a great necessity and an asset to many industries and business processes. This is primarily because of the information and measurements it provides in monitoring of various industrial processes. This helps in operational and maintenance decision-making process which is crucial for sustainable growth. The low powered wireless sensor network offers the possibility of remotely controlling and monitoring for one such industrial process, viz. metal-fill monitoring for the Lost Foam Casting process. This thesis is primarily focused on improving the performance of metal-fill monitoring using the wireless sensor network developed at the Tennessee Technological University. The thesis addressed two key requirements of typical industrial environments: power efficient monitoring for energy constrained wireless sensor network and reliable data transmission in the lossy wireless environment.In this thesis, the problem of energy efficient communication associated with the wireless sensor network has been explored and intelligent fuzzy transmission power controller was proposed. The proposed algorithm was then put to test in an actual real world scenario. The results of the experiments showed that the algorithm was capable of maintaining the radio transmission power at an optimal level. The issue of wireless data transmission reliability was studied and a new integrated algorithm was investigated. The new algorithm was an integration of two different techniques namely the Cauchy Reed Solomon Coding and the Delayed Retransmission technique.Tests were carried out in a foundry environment to evaluate the effectiveness of the two algorithms proposed. The fuzzy controller was able to maintain radio transmission power at an optimal level. The integrated data transmission algorithm was able to maintain reliable data transfer even in a very harsh environment.