This is a submission for the Nylas Challenge: Galaxy Brain.

What I Built and Why

This project is a comprehensive IoT-based system designed to detect and mitigate forest fires and illegal logging activities. The motivation behind this project stems from the alarming statistics surrounding deforestation and forest fires.

Globally, illegal logging accounts for up to 15-30% of all wood traded, contributing significantly to deforestation. Every year, approximately 15 billion trees are cut down, which leads to a loss of biodiversity, disruption of ecosystems, and increased carbon emissions. Forest fires, another critical threat, destroy nearly 4.2 million square kilometers of forested area annually, releasing massive amounts of carbon dioxide and other pollutants into the atmosphere.

The implementation of IoT systems like the one developed in this project can play a crucial role in reducing these devastating effects. By providing real-time monitoring and early detection of forest fires and illegal logging activities, such systems can enable quicker response times, potentially reducing forest fire damage by up to 50% and illegal logging by a significant margin.

Through this project, I aimed to build an integrated system that not only detects these activities but also automates the process of notifying relevant authorities, marking incidents on a calendar, and analyzing data through a user-friendly dashboard.

Demo

Below is a YouTube Video to a demonstration of the system.

Code

You can find the complete codebase for ForestWatch project here. Feel free to create an issue suggesting new features you would like to see in the project.

Your Journey

Throughout this project, integrating Nylas played a pivotal role in achieving the goal of creating an automated and responsive forest monitoring system. Leveraging the Nylas APIs enabled seamless communication and notifications, which are essential for real-time forest management and response to illegal activities.

I utilized the Nylas API to automate the process of notifying authorities whenever a potential forest fire or deforestation activity was detected. The API allowed me to fetch contact information (using contacts API) of relevant authorities dynamically and send them immediate email alerts (using email API). This integration was crucial in ensuring that the right people were informed at the right time, potentially reducing the response time to these incidents.

Furthermore, Nylas was instrumental in scheduling calendar events to log when illegal activities occurred(using calendar API). This automated tracking ensured that the timeline of events was meticulously recorded, helping in the analysis and understanding of patterns related to forest crimes.

One of the most rewarding aspects of this journey was learning the intricacies of the Nylas API and understanding how it could be used to bridge the gap between IoT data and actionable responses. Implementing these features has given me a deeper appreciation for how technology, such as Nylas, can be harnessed to create meaningful impact in environmental conservation.