The increasingly serious water pollution problem makes efficient and information-based water quality monitoring equipment particularly important. To cover the shortcomings of existing water quality monitoring methods, in this paper, a mobile water quality monitoring system was designed based on LoRa communication and USV. In this system, the USV carrying water quality sensors was used as a platform. Firstly, the LoRa network is used to monitor water quality over a large area. Secondly, the unmanned surface vessel controls the position error within ±20 m and the velocity error within ±1 m/s based on the Kalman filter algorithm. Thirdly, the genetic algorithm based on improved crossover operators is used to determine the optimal operational path, which effectively improves the iterative efficiency of the classical genetic algorithm and avoids falling into local convergence. In the actual water surface test, its packet loss probability within a working range of 1.5 km was below 10%, and the USV could accurately navigate according to the preset optimal path. The test results proved that the system has a relatively large working range and high efficiency. This study is of high significance in water pollution prevention and ecological protection.

In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.

In order to comprehensively improve the sensitivity of fire warning and effectively shorten the warning time, this paper proposes and implements an indoor distributed fire alarm system based on low power wide area network. The system is mainly composed of three parts: a multisensor acquisition node based on LoRa technology, a distributed edge gateway, and a remote user monitoring system. The multisensor collection node obtains environmental parameters such as indoor temperature, smoke concentration, and air quality and then transmits the sensing data to edge gateway by LoRa after preprocessing. The edge gateway is based on an embedded Linux platform and is deployed in distributed state to collect and store data from multiple collection nodes. Besides, edge gateway forwards valid data to the remote user monitoring system by standard MQTT protocol. The user monitoring system displays current deployment area parameters to users in real time and provides early warning prompts based on relevant preset indicators to help the administrator make more accurate decisions on corresponding measures. The system has been deployed and tested in Nanjing Institute of Technology. By sensor calibration experiments, LoRa communication experiments, and system tests in different environments, the experimental results show that the average received signal strength in a small interference space is -104.12 dBm, and the average received signal strength in a noisy signal environment is -57.5 dBm. By setting the optimal transmitting power for each distance, the packet receiving rate can reach more than 95%, and the alarm accuracy can reach 100% under premise of ensuring the lowest power consumption. Finally, this paper conducts a comprehensive performance analysis on the wireless communication performance of environmental collection nodes, multisensor data fusion algorithm, distributed LoRa edge gateway deployment performance, and remote system early warning accuracy.

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A new hydraulic drawing system of coal mining machine is proposed in this paper. The variable plunger pump adopted in the hydraulic drawing system of coal mining machine is replaced by load-sensing variable displacement pump. The working principle and energy-saving of the new system are introduced. The performance of the new system is obtained by the simulation study using AMESim.