Design and experiment of an online monitoring system for peanut seeding parameters based on IoT

Aiming at the problems in the traditional peanut sowing operation process, such as single monitoring mode, lack of online monitoring function, inability to deeply utilize data, and difficulty in tracing the sowing quality, an online monitoring system for peanut sowing parameters based on the Internet of Things (IoT) was designed. The online monitoring system for peanut sowing parameters consists of a peanut seed-metering monitoring device, an on-board monitoring terminal, and an online monitoring cloud platform. The system can monitor parameters such as seed spacing, seeding rate, missed seeding, vehicle speed, temperature, and humidity. It transmits data through RS485 and IoT communication, and supports local interaction and cloud data storage and analysis. The seed-metering monitoring device uses laser opposite reflection and window fiber optic sensors to monitor the missed seeding and seed-metering status in real time. The on-board terminal uses an optoelectronic rotary encoder to collect the rotational speed and calculate the parameters. The operation status is displayed through the human-machine interaction module, and the data is packaged and sent to the cloud server via a wireless network. The online monitoring cloud platform selects the Alibaba Cloud IoT platform, connects with it through the MQTT protocol, and conducts visual development using IoT-studio to achieve data display, analysis, and statistics. Through the test on the simulated test bench, the accuracy rates of the seed spacing, seeding rate, and missed seeding monitoring of the seed-metering monitoring module of the system exceed 98.02%, 98.03%, and 99%, respectively. The field test based on the actual seeder shows that the monitoring effect of the seed spacing of 16 cm and 20 cm is good. The accuracy rate of the 27 cm seed spacing decreases slightly with the increase of the speed but still exceeds 97%. The accuracy rates of the missed seeding and seeding rate monitoring exceed 98%, and the online monitoring module transmits data normally. After testing, each part of the system has good performance, meeting the functional and accuracy requirements of the online monitoring of peanut sowing operation parameters.