IOT Based Smart Agriculture System

Remote Control, Monitoring and Data collection System for Agricultural lands. Using telegram bots and AWS cloud services.

Librería que hace análisis estadístico de datos de humedad y temperatura de un cultivo hidropónico. (media, desviación estándar, y cálculo de veces dentro de rango de condiciones óptimas para el cultivo)

The project is about smart agriculture and is a system that allows people to monitor the status of their cultivated areas by automatically managing irrigation. The network consists of a border router, an undefined number of scattered nodes throughout the lands and a central server (the Master) that coordinates and manages all nodes.

lightWay - choose the right way × 1st Place @ PoliHack 2021 (Juniors)

PlantPulse helps users monitor their crop fields in real-time using IoT, and recommending the most suitable crops using an ML model. 🚜🌾💧

Precision Farming Robot using ESP32 for motor control and live video streaming. Controlled via MQTT and a GUI, this system aims to automate farming tasks for smart agriculture.

Embrace limited and imperfect training datasets in plant disease recognition using deep learning.

Official code of the paper "Deep-Wide Learning Assistance for Insect Pest Classification"

AgroSmart- The Smart Agriculture

And IoT project on Smart Agricolture

UrbanKisaan 🌱 - A web app designed to empower urban farmers with tools to track soil health, monitor crops, and connect with a thriving farming community. 🚜💻

Academic application ReactNative | Firebase

The Smart Plant Monitoring System is an IoT project that automates plant care using an ESP32 microcontroller. It monitors soil moisture, temperature, and humidity, automating watering based on sensor data. The system connects to the Blynk app for remote monitoring and control, making it perfect for smart agriculture or home automation.

NRF52 BLE Agriculture example

The main objective of this internship was to approach in general the topic of the use of classical Machine Learning and Deep Learning techniques for intelligent agriculture with a focus on the optimization and improvement of agricultural production.

AI-Models for Smart Irrigation System

Docker environment for analyzing Argentina agriculture production data.

Este projeto implementa um sistema de irrigação automática utilizando um ESP32 para monitorar a umidade do solo e controlar um relé, garantindo a eficiência no uso da água. Os dados coletados pelos sensores são exibidos em um dashboard desenvolvido com Flask, permitindo o monitoramento remoto das condições do solo e do ambiente.