A small-scale model house evaluation platform for building automation systems

Burkert, Malte; Esdohr, Jorn; Krumm, Heiko

doi:10.1109/etfa.2016.7733690

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The size of a room at home is very varied, as needed. But the average requirement of the house area ranging from 2, 3 and 4 square meters [19,20]. So this research used 3 square meters as a case study, that is an average area at house room.…”

Section: Methodsmentioning

confidence: 99%

WSN performance based on node placement by genetic algorithm at smart home environment

et al. 2019

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Wireless sensor connectivity is one of several factors that determines the communication reliability of each node. The placement of the node depends on the area that covered by wireless coverage area, so the node placement should be optimally placed. But the other aspect is the sensor coverage area. Sensor coverage area sometimes could be different with wireless sensor coverage area. Based on that situation, it needs to optimize that situation. Genetic Algorithm is an algorithm that utilizes a heuristic approach that uses biological mechanism evolution. It used to evolution the best position of Sensor Node based on Wireless and Sensor coverage area. After the position of each node generated by Genetic Algorithm, it still needs to evaluate the wireless sensor node performance. The performance indicates that the genetic algorithm can be used to determine sensor node placement in the smart home environment. The smart home environment used to monitor event at the house such as wildfire. In this research used Quality of Services (QoS) to measure wireless sensor performance. The experimental testing scenario will be used to place several nodes that generated. The QoS performed systems reliability that produced based on 3, 4 and 5 testing nodes, the minimum and maximum of each: delay is 6.21 and 8.74 milliseconds, jitter is 0.11 and 1.59 Hz and throughput is 68.83 and 90.49 bps. Based on ETSI classification, the performance of sensor node placement is Good and acceptable in real-time systems.

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Section: Methodsmentioning

confidence: 99%