Intelligent, IoT-based greenhouse automation system with real-time monitoring, control, and alerts.

Abstract

A greenhouse automation system consisting of several sensor nodes for measuring temperature, humidity, soil moisture, and light intensity; one or more control modules, including an ESP32 and an Arduino Uno, that acquire sensor data and control water pumps, exhaust fans, and LED lights according to configurable thresholds with hysteresis; a LoRa transceiver for transmitting measured values ​​and receiving commands via a long-range wireless connection to a gateway; and a GSM module for transmitting real-time alerts to user devices.

Description

Application area of ​​the invention

[0001] The invention relates to agricultural automation systems that monitor and control greenhouse environments using networked sensors, embedded controllers and long-range wireless communication for remote alerts and cloud-based monitoring. Background of the invention

[0002] The productivity of greenhouses depends on maintaining optimal temperature, humidity, soil moisture, light, and CO2 levels, as well as related factors. Manual control is time-consuming and prone to errors. IoT-based systems utilize sensors and actuators coordinated by microcontrollers. Studies report the use of ESP32 / Arduino platforms with environmental sensors to automate irrigation, ventilation, and lighting, as well as to provide remote dashboards and alerts. Long-range connections such as LoRa and LoRaWAN are widely used in agriculture due to their low power consumption and range of several kilometers, supporting distributed nodes and cloud analytics.The integration of cost-effective controllers, LoRa telemetry, GSM alerts and cloud storage into a coherent, scalable system specifically tailored for greenhouse operation addresses reliability, coverage and cost constraints. Summary of the invention

[0003] The invention relates to a greenhouse automation system with sensor nodes for measuring temperature, humidity, soil moisture, and light intensity; control modules based on ESP32 and Arduino Uno for data acquisition and local control; a LoRa radio link to a gateway for data transmission over longer distances; and a GSM module for real-time notifications to the user in the event of critical incidents. Actuators such as water pumps, exhaust fans, and LED grow lights are automatically controlled based on threshold values ​​or control logic, while cloud storage and an Android app enable real-time visualization and remote control.

[0004] In various configurations, the system applies control guidelines with hysteresis to prevent disturbances, prioritizes energy efficiency through cyclical control of radio devices and actuators, and optionally supports AI-based predictive analytics to anticipate irrigation and ventilation needs based on historical trends and weather forecasts. The modular architecture allows for scaling from a single greenhouse to facilities with multiple houses and centralized dashboards. Detailed description

[0005] The sensor nodes comprise temperature and humidity sensors, soil moisture probes, and light sensors, placed at representative locations in the canopy and soil to capture microclimate variations. Each node is connected to an ESP32 or an Arduino Uno with an ESP32 gateway and collects data at configured intervals with local filtering and calibration. The data packets contain timestamps and node IDs and are sent via LoRa to a gateway, which forwards them to a cloud endpoint. LoRa was chosen for its long range and low power consumption, making it suitable for greenhouses and agricultural facilities.

[0006] The controller uses threshold-based regulation and hysteresis bands to control pumps, fans, and lights, and supports schedules as well as manual overrides. Control rules are configurable via the app and include safety interlocks to prevent pumps from running dry and fans from bouncing. Soil moisture control uses volumetric thresholds to trigger irrigation windows with maximum run times, thus preventing over-watering. Lighting control uses LDR-based intensity adjustment and schedules to supplement daylight.

[0007] A GSM module delivers SMS / voice alerts for critical conditions such as overheating, insufficient soil moisture (below the permissible limit), power outages, or loss of communication. The alerts include current measurements and a link to the dashboard for remote control. The Android app displays live graphs, historical trends, and actuator status, and enables remote control with role-based permissions.

[0008] Communication takes place via a star topology: Multiple sensor / actuator nodes send LoRa uplinks to a greenhouse gateway, which can run on an ESP32 or a single-board computer and is connected to the cloud via Ethernet / Wi-Fi / cellular. Downlinks transmit configuration updates and actuator commands. Duty cycling, confirmed message policies for alarms, and adaptive data rates ensure a balanced ratio between reliability and energy consumption.

[0009] Cloud storage preserves time-series data for analysis and reporting. Optional forecasting modules use historical data to predict irrigation needs or aeration events; dashboards provide recommendations and can automatically approve actions according to user-defined policies. The system supports multi-tenant views for farms with multiple buildings.

[0010] The energy management system includes efficient drivers for pumps and fans, MOSFET / H-bridge control, and load monitoring for fault detection. Solar batteries can power distributed nodes and feature monitoring timers as well as local fallback functions for safe states in case of connection loss. Environmentally friendly enclosures protect the electronics from moisture and dust.

[0011] Security measures include device authentication, encrypted transmission between the gateway and the cloud, and signed firmware updates. Local logs and cloud audit trails capture activation and alarm events for traceability.

[0012] In normal operation, sensors send readings to the controller. If the temperature exceeds a setpoint, the fans switch on until the readings fall below the lower hysteresis limit. Low soil moisture triggers pump cycles; dim light activates LEDs according to a schedule. Critical deviations result in GSM alerts and app notifications. Operators can view the history and adjust thresholds remotely.

[0013] The architecture allows for the integration of additional sensors (CO2, pH / EC in hydroponics) and supports expansion for precise fertilization through connection to dosing pumps. Modules for predictive analytics optimize target values ​​seasonally to increase yield and resource efficiency.

Claims

[1] A greenhouse automation system consisting of several sensor nodes for measuring temperature, humidity, soil moisture and light intensity; one or more control modules, including an ESP32 and an Arduino Uno, which acquire sensor data and control water pumps, exhaust fans and LED lights according to configurable thresholds with hysteresis; a LoRa transceiver for transmitting measured values ​​and receiving commands via a long-range wireless link to a gateway; and a GSM module for transmitting real-time alerts to user devices. [2] The system according to claim 1 further comprises a cloud service configured to store time series data, provide dashboards and remote control via an Android application and distribute configuration updates to the controller modules. [3] System according to claim 1, wherein the control modules implement an energy-efficient duty cycle of radio devices and actuators, safety interlocks including dry-running protection of the pump and debounce protection of the fan, and a backup operation to maintain safe environmental conditions in the event of loss of connection. [4] System according to claim 1, wherein the system supports optional AI-based predictive analytics configured to forecast irrigation and aeration needs based on historical trends and environmental data and to suggest setpoint adjustments for proactive plant management.