Design Problem

The Living Planet Report, a comprehensive overview of the state of the natural world, reveals global wildlife populations have shrunk by an average of 73% in the past 50 years. Conservationists struggle to accurately quantify the population sizes of various species due to a lack of resources and the remote settings where they live.
The Convention on Biological Diversity (CBD) is the international legal instrument for “the conservation of biological diversity, the sustainable use of its components and the fair and equitable sharing of the benefits arising out of the utilization of genetic resources” that has been ratified by 196 nations.
According to UNDP, a new nature-positive economy could generate up to $10.1 trillion in annual business value and create 395 million jobs by 2030. This $10 trillion of business opportunities could be unlocked by transforming the economic systems that are responsible for almost 80% of nature loss: food, infrastructure, energy and extractives.
Technology offers potential for collecting data and processing images in real-time.

I want to design a camera trap system that uses local AI image processing to identify species/animals, and send the identification data wirelessly to a central dashboard.

Design Process

Automated, Cost-Effective Monitoring: The project provides a more accessible and affordable method for wildlife monitoring. Traditional methods of tracking species, such as sending field researchers or using large-scale surveillance systems, are often costly and labor-intensive. The proposed camera traps are relatively low-cost, can be deployed in remote areas, and work autonomously, significantly reducing the need for human involvement and long-term operational costs.

Data Collection for Conservation: Conservationists need up-to-date, accurate data to make informed decisions. The camera traps, powered by AI, continuously collect data on species sightings and upload them once a day. This allows conservation teams to quickly detect changes in species presence or population size and take immediate action. For instance, if poaching becomes a problem in a particular area, from camera traps could help park rangers pinpoint the threat.

Monitoring in Remote and Challenging Environments: Many endangered species live in remote areas that are difficult to access, such as deep forests, savannas, or mountainous regions. The camera traps, equipped with AI and capable of uploading data via mobile broadband or satellite, are ideal for such environments. They provide a non-invasive, remote solution that can operate in challenging terrains, ensuring that even the mostb hard-to-reach ecosystems are monitored.

Global Applications for Endangered Species: The project has global relevance because it can be deployed in various regions, from the savannas of Africa to rainforests in South America, and even temperate zones. Different species, including large animals like elephants and tigers, as well as smaller creatures like insects and birds, can all be tracked. This global applicability makes it a versatile tool for addressing biodiversity loss across the world.

Link to Process Journal and Final Reflection Video

https://docs.google.com/document/d/1AuaOSSFPVjpy886V7A2-U1WcJAHvjQsDbhzSeQqGKUU/edit