PyCon 2020 Talk: "How to build an intelligent “indoor garden” with microcontrollers, CircuitPython, and IoT."

parallel garden project - IoT and hydroponics monitoring

IoT Smart Garden 🌱

Eduponics Raspberry Pi MQTT Library - build your smart IoT garden with ease.

An IOT project to help users monitor their indoor garden and operate various tasks like watering the plant, controlling the room temperature or the moisture of the air.

🌿 IoT dashboard for smart garden

Automated garden system for my office

A smart device connected to a plant, which measures the soil moisture level, the ambient temperature and humidity and based on the data collected it waters the plant to meet its needs. The data is published online and a web interface allows direct interaction with the gardening station.

Smart Garden IoT Project

This is our smart city project using IOT Controllers in Cisco Packet Tracer and also we made demo of smart garden and home automation using Google Assistant (Triggered by only say OK GOOGLE) and micro controllers.

Usage: This project contains a python script called people_detection.py, a folder named haarcascades and two test videos. The download links for the two test videos are: Test_video_1.mp4: https://github.com/intel-iot-devkit/sample-videos/blob/master/worker-zone-detection.mp4 Test_video_2.mp4: https://www.pexels.com/video/man-transporting-garden-sand-using-a-cart-7714807/ You need execute the following statement to run the python script. > python3 people_detection.py -v ./test_video_1.mp4 -face_detec False The python script needs to pass in two parameters, namely “-v” and “-face_detec”, where “-v” refers to the video path that needs to be tested, and “-face_detec” refers to the need for face detection(If there is no face in the video, set to False). This python script first modifies the shape of each frame in the video, then performs corner detection, and then performs optical flow tracking on the detected corners, then execute human detection and face detection in turn, and draws frames and ellipses on the image respectively in.

IoT enabled Garden Management System backed by AI

No description available

This is an InternetOfThings(Iot) application, primarily developed to capture photographs of birds (could be squirells, rodents etc !!) visiting the garden bird feeder. The Iot PIR sensor detects any motion when birds land on the feeder, sends a notification to an android app to activate the phone's camera shutter and click an image of the bird(s). We could however extend the use of this app in other ways such as a security camera.

IoT device using combination of ARM STM32F4 and wireless device ESP8266-01. ARM device collects environtment data such as temperature, humidity, soil humidity from sensors, reads data, converts into readable data. These data pushed to webservice (use PHP) by ESP8266 device. All information showed on Android application. We can check environment real time and control to water your garden.

No description available

The aim is to keep the plant alive

Index for the GrowSense garden/farm/agriculture monitoring and automation IoT device range.

Jarvis is an IoT system that includes a main unit, an outdoor unit and an optional server. The main unit is a smart thermostat can communicate with the server and the external unit, it can download weather forecasts from wunderground.com site and is controllable via Blynk for Android and iOS. The outdoor unit will have supplied a temperature sensor, a humidity and a solenoid valve to control irrigation of the garden.

This repository consists of files required to set up an IoT system, based on an Arduino Yun board, which manages the automatic irrigation of a small vegetable garden, depending on the detection of environmental conditions (temperature, humidity & moisture) and the choice (by the user) of a particular crop to be managed. Notification of all the data and possible alarm situations through a dynamic and interactive web page and a e-mailing system. Arduino Yun works as a web server by locally hosting from the microSD card.

🌱 An IoT + AI Garden Monitor // Admobilize Matrix Creator + Visa API 🌱

Let's turn the garden into an I(o)T problem!

IoT - smart garden using ESP32 microcontroller, mqtt protocol, nginx, influxdb and node-red

The main objective is to provide a comfortable and convenient user interface by sensing and controlling the plant environment. Using Node MCU along with several sensors like soil moisture, Temperature and Humidity sensor were used to actuate water pump and UV light source. Which interact with an android app using Ubidots as a cloud platform. The project successfully completed under the supervision of Experts Hub team, Pune.

As part of the IoT application development project I designed a way in which user's can control their smart garden through a mobile app. This repo contains the code needed for the Raspberry Pi backend.

This project is one application of IOT project. This is Automatic watering system. This project includes Arduino uno, relay, bluetooth module, gsm module, Motor (From fishing aquarium), jumper wires, Soil humidity sensor. It can be planted in the garden near your house or just in a small plant pot. The motor should be kept in water reservoir, and a pipe needed to bring the water to the plant. Then if the soil has less humidity it will water the plant automatically. If you want to add more water or add water as per your need. You can open the application which i have made using MIT APP INVENTOR. You connect the app to system using bluetooth and can water manually. It will send back the time and date of watering back to the bluetooth module. Similarly you can message to the number installed in gsm module to water the plant if you are far from the system. To water the plant using gsm module you need to message it with "s" character and it will water the plant.

IoT kitchen garden system for using various sensors and Google Cloud services.

IoT Smart Plant Monitoring System

Raspberry Server that controls a garden using AWS IoT

The IoT-Based Plant Disease Recognition System is designed to help farmers, gardeners, and researchers detect plant diseases early. It combines IoT hardware, web technologies, and AI-based image analysis to automate plant health monitoring.