A triboelectric nanogenerator with efficiency enhancement based on relative inversion for smart agriculture

The emergence of smart agriculture has enabled functions such as agricultural visualization, remote control, and disaster forecasting. In the process of smart agriculture construction, a substantial number of sensors are typically required to effectively monitor environmental parameters. In this study, a high-power density double-rotor triboelectric nanogenerator (DR-TENG) integrating wind energy harvesting and environment monitoring is introduced, by which the relative velocity between the two rotors is augmented through rotational reversal, thereby enhancing output performance and monitoring accuracy. By virtue of this mechanism, the output current witness a remarkable enhancement of 76.7 ​% under the wind speed of 4 ​m/s. There is an excellent linear correlation coefficient (99.9 ​%) between the signal frequency of DR-TENG and the excitation wind speed, indicating that the DR-TENG exhibits exceptional sensing performance. The present study establishes a wireless sensing system for smart agriculture based on DR-TENG, which integrates a power supply circuit, signal processing circuit, temperature sensor, and Zigbee module, enabling self-powered real-time monitoring of wind speed and temperature. Additionally, the DR-TENG can be used to recognize humidity. The accuracy of humidity recognition based on deep learning model reaches 98 ​%. This work presents an efficient and viable method for wind energy harvesting and environment monitoring.