Gao Peng

TL;DR: In this article, a deep bidirectional long short-term memory (Bid-LSTM) networks are proposed to improve soil moisture (SM) and soil electrical conductivity (SEC) predictions, providing a meaningful reference for irrigation and fertilization of citrus orchards.

TL;DR: In this article, a random forest model was developed using sample data derived from meteorological measurements including air temperature, relative humidity, wind speed, and photosynthetic active radiation (Par) to predict the lower baseline (Twet) and upper baseline (Tdry) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2).

TL;DR: Results showed that the GA-BP neural network model can express the nonlinear relationship between the water demand of litchi and the main environmental factors more accurately and can provide a theoretical basis for the further development of the intelligent irrigation decision system of litchesi orchards.

TL;DR: In this paper, an automatic irrigation system for mountain region fruit tree, including a M irrigation node, gateway, server, wherein every is irrigated node and all including first processor, still including the environment detection unit, a communication unit, electromagnetism valve control unit, the positioning unit that are connected with first processor respectively, the gateway includes second processor, and the water pump be connected with second processor respectively.

TL;DR: In this paper, an unmanned aerial vehicle gateway device for mountain region citrus orchard environmental information acquire, including processor module, power module, 2.4GHz wireless control module, barometer module, motion sensor module, zigBee module and GPRS module.