• Project summary
  • The issue we are hoping to solve
  • How our technology solution can help
  • Our idea
• Technology implementation
  • IBM AI service(s) used
  • Other IBM technology used
  • Solution architecture
• Presentation materials
  • Solution demo video
  • Project development roadmap
• Additional details
  • How to run the project
  • Live demo

The Ecoest project is an attempt at employing IOT and AI Technology to boost Forest Bio Diversity Conservation efforts in Kenya.

Our solution enables:

• Real-time data collection and analysis to increase visibility and monitoring of forest conditions
• Helps inform conservation efforts by logging all ongoing reforestation projects.
• Prevent spread of Wild Fires through early detection

Our solution is a Web Based iot powered forest monitoring system. It features Automated Forest Monitoring System enabled by custome IOT, A Comprehensive Dashboard with Real Time Data on climatic conditions using Node Red and an Automated Fire Monitoring System & Alerts service.

• IBM MQTT is used in this project to send messages form the device to our node red server. Using the publish/subscribe mechanism we are able to publish sensor readings that can be displayed on the APP
• Node-RED Node-Red is used to create an interactive map displaying all identified forest reserves targetd by this project for monitoring.

Diagram and step-by-step description of the flow of our solution:

1. User visits Ecoest App through an Angular App client
2. The device takes temperature, humidity and gas readings every 20 minutes
3. MQTT client publishes readings through MQTT Broker to the node-red server.
4. Node-red publishes the data onto Ecoest Backend for analysis and Storage.
5. Backend responds to client request with received data from node-red server

INSTRUCTIONS: The following deliverables should be officially posted to your My Team > Submissions section of the Call for Code Global Challenge resources site, but you can also include them here for completeness. Replace the examples seen here with your own deliverable links.

The project currently does the following things.

• Performs real time monitoring of identified forest reserves using IOT devices
• Provides visibility on Community Based Reforestation Projects

In the future we plan to...

• Develop a prediction model on deforestation using data sources gathered during the challenge and with the help of open source data by initiatives such as tha JICA REDD+ project.

See below for our proposed schedule on next steps after Call for Code 2023 submission.

• cd eco-frontend
• npm install
• npm run start

• cd ecoest
• python -m venv venv
• source venv/bin/activate
• pip install -r requirements.txt
• python manage.py migrate
• python manage.py runserver