Abstract: In order to solve the problem of high power consumption and limited node energy in the existing aquaculture water quality monitoring system, a low-power aquaculture water quality monitoring system is designed. For wireless testing nodes, cycle adaptive adjustment algorithm is used to reduce the number of data transmission and power adaptive adjustment algorithm is used to reduce power consumption. For the testing gateway, NB-IoT technology is mainly used to reduce wireless transmission power consumption and FreeRTOS real-time operating system is carried to increase the CPU utilization to reduce power consumption. Experiments show that under the condition that significant change data is not lost, the number of data transmission is reduced by 140% and 20% respectively for using cycle adaptive adjustment algorithm and using fixed cycle 15 min and 30 min. Under the condition that packet loss required by the system is satisfied, power consumption for using the node of power adaptive adjustment algorithm is 9.5%-42.5% less than that for using the node of fixed transmit power 4 dBm. Experimental results show that the system has the characteristics of low power consumption, high stability, sensitive remote control, and has a high application value.

Key words: Aquaculture, water quality testing, adaptive adjustment algorithm, NB-IoT, Low power consumption

摘要： 为解决现有水产养殖水质监测系统中功耗高、节点能量有限的问题，设计了一款低功耗水产养殖水质监测系统。对于无线检测节点，主要采用周期自适应调节算法减少数据发送次数和功率自适应调节算法降低功耗；对于检测网关，主要采用NB-IoT技术来降低无线传输功耗和搭载FreeRTOS实时操作系统提高CPU利用率的方式降低功耗。通过试验测得，在不丢失重要变化数据的条件下，采用周期自适应调节算法与采用固定周期15 min和30 min相比，数据发送次数分别减少了140%和20%；在满足系统要求丢包率的条件下，采用功率自适应调节算法的节点要比采用固定发射功率4 dBm的节点功耗降低9.5%~42.5%。结果表明，本系统具有功耗低、稳定性高、远程控制灵敏的特点，具有较高的应用价值。

关键词: 水产养殖, 水质检测, 自适应调节算法, NB-IoT, 低功耗