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An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
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An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
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An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search

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An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search
Journal Article

An improved k-angle coverage algorithm for multimedia wireless sensor networks based on two-layer tabu search

2022
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Overview
The multimedia Internet of Things system is helpful for real-time monitoring and research of vegetable growth status and related environmental variables in the greenhouse. However, dense interleaved growth of vegetables can create a blind area of multimedia sensors. Different vegetable angle views also have different characteristics. The single-angle view cannot accurately obtain the concerned status information. The traditional multimedia sensor coverage mainly focuses on making the sensing region contain as many targets as possible, but the monitoring view and quality cannot be guaranteed due to the limited view angle and visual occlusion. Based on the actual needs, this paper studies an angle coverage judgment method based on the sensor set. By analyzing the topological relationship between each target and each corresponding sensor set, a multi-objective optimization function including angle coverage and area coverage is established, which can monitor the planting region from k angles. To solve this function, this paper then designs a two-layer code solution based on the traditional tabu search algorithm framework and adopts adaptive local search to improve the global search. Experimental results show that the judgement method in this paper is more efficient than other methods. The studied algorithm can converge to the excellent solution and obtain a small node set covering the target region from multiple angles as much as possible, thus improving the monitoring quality of vegetable greenhouse.