Remote Monitoring and Management Control System Solution for Smart Agriculture Based on LoRa Gateway

WideIOT provides a smart agriculture solution based on the LoRa gateway, enabling real-time remote monitoring and management control of agricultural sites.

 This solution enhances the accuracy and timeliness of agricultural management while strengthening the ability to respond to abnormal meteorological disasters and pest risks, effectively improving agricultural production efficiency and product quality.

The solution consists of terminal nodes, a LoRa gateway, and a smart agriculture platform.

 Terminal nodes include sensors for carbon dioxide, rainfall, soil moisture, light intensity, temperature and humidity, water level, as well as Programmable Logic Controllers (PLCs) for equipment such as irrigation, supplemental lighting, and ventilation systems. The LoRa gateway collects data from these terminal node devices and uploads it in real-time to the smart agriculture platform, enabling functions such as data monitoring, abnormal alarms, remote control, device management, and data analysis.

The LoRa gateway employs a polling method for data collection, akin to having one-on-one conversations with a group of people sequentially to avoid overwhelming the devices and platform with excessive data simultaneously, ensuring smooth communication and data interaction.

 For data upload to the cloud, real-time communication with the platform is achieved via 4G wireless networks, allowing for data reading and device control on the cloud platform. In this context, device control commands take precedence over data collection commands to ensure timely manipulation of irrigation, lighting, and ventilation equipment to intervene in crop growth environments.

Leveraging a WeChat mini-program, users can access meteorological data (such as field temperature and humidity, soil moisture, water level, carbon dioxide, rainfall, and light intensity) and device data (including the on/off status, voltage, and current of irrigation, lighting, and ventilation equipment) from various agricultural sites anytime and anywhere.

 By setting alarm thresholds and notification methods, users can swiftly inspect and address agricultural emergencies, employing remote control measures for management, such as remotely activating irrigation pumps and shutting them off once soil moisture reaches equilibrium, ensuring optimal water conditions for crop health.

Through timely management operations based on various data points, a decision-making framework for agricultural big data analysis can be constructed. This framework provides effective operational plans and solutions when facing meteorological disasters, pests and diseases, equipment failures, or malicious damage, enabling prompt responses to minimize losses and waste.