At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using\nwireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and\nlatency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless\nsensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing.\nSecond, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and\ncorrelation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best\nnode and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection\nalgorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the\nproposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison\nresults, the proposal outperforms the traditional methods in metrics.
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