Smart Agricultural Monitoring and Automated Irrigation through an IoT-Based Wireless Sensor Network using ESP32: A MATLAB Analysis

The advancement of agricultural technologies in Honduras is paramount to bolster productivity in the sector. Embracing cutting-edge solutions like Internet of Things (IoT) and ESP32 microcontrollers holds the potential to elevate crop quality, foster innovation and competitiveness, slash production costs, and drive rural development. Leveraging sophisticated tools such as MATLAB enables farmers and agricultural experts to harness mathematical matrix analysis for informed decision-making based on real-time data from a network of wireless sensors integrated into this prototype. Accessible through the Blynk platform, this streamlined approach marks a significant stride towards harnessing advanced technologies to revolutionize agriculture and uplift the livelihoods of Honduran farmers. The integration of IoT and Precision Agriculture (PA) technologies is vital. A centralized online platform tailored for Honduran farmers allows seamless access to real-time data from wireless sensors, covering crucial factors like weather conditions and crop health. The prototype's sensing data on coffee cultivation yielded 1000 data entries, which were analyzed to demonstrate consistent alignment with crop growth-promoting variables. Air temperature consistently ranged between 20 degrees C and 24 degrees C, which is the ideal range for coffee plants. Air humidity remained between 70% and 80%, suitable for effective transpiration and nutrient uptake. While pH levels regularly dropped between a recommended range of 5 and 7, ensuring nutrient availability, soil moisture readings consistently ranged from 60% to 80%, supporting healthy root systems and enabling nutrient absorption. The analysis of over 1,000 data entries confirms the effectiveness of IoT and PA technologies in addressing Honduras' agricultural challenges. Correlation with MATLAB enhances data credibility, facilitating better decision-making for agricultural progress.