At age 17, Indian-American student Anika Puri developed a $300 AI-powered tool to help wildlife rangers spot potential elephant poachers. Her invention, ElSa (Elephant-Savior), uses artificial intelligence and thermal drone footage to distinguish between human and animal movement patterns. During testing, the system achieved 90.9% accuracy in detecting humans. Her work also earned her a $25,000 Davidson Fellows Scholarship in 2022.
Who Is Anika Puri?
Anika Puri is an Indian-American researcher and technology innovator from Chappaqua, New York, who developed an interest in science, robotics, and engineering at a young age. Her interest in wildlife protection began during visits to India. While visiting markets in Mumbai, she noticed ivory jewelry and decorative items being sold. This made her curious about elephant poaching and the challenges involved in protecting endangered animals.
As she learned more about the problem, Puri discovered that wildlife rangers use drones equipped with thermal cameras to monitor wildlife reserves and other protected areas at night. However, checking hours of drone footage can take a lot of time and effort. She wanted to find a simpler and more affordable way to help rangers. This idea led her to develop ElSa, an AI system that could help identify human activity in wildlife areas.
What Is ElSa, Anika Puri’s AI Wildlife Protection System?
ElSa, short for Elephant-Savior, is an AI-powered system that uses thermal drone footage to detect human movement in wildlife areas. Thermal cameras detect infrared radiation emitted by objects, allowing them to capture heat patterns and help identify people and animals in darkness. However, it can be difficult to tell them apart, especially when drones record footage from high above the ground.
To solve this problem, Puri created ElSa to study how people and animals move. Instead of relying only on their appearance, the system looks at their speed, direction, and movement patterns. This helps wildlife rangers spot possible human activity in protected areas without watching every minute of drone footage. However, ElSa cannot confirm whether someone is a poacher. Rangers still need to review the footage and investigate anything suspicious.
How Does Puri’s AI System Detect Potential Poachers?
Monitoring large forests and national parks is difficult, especially at night. Drones make the job easier by recording footage from above, but reviewing hours of videos can take a lot of time. Puri developed ElSa to help rangers with this task. The system uses AI to study movement in thermal videos and identify differences between humans and animals. It looks at movement characteristics, including:
- Movement speed: How fast a person or animal moves.
- Turning radius: The radius of the path an object follows when turning.
- Movement patterns: How they move from one place to another.
- Herd behaviour: Whether animals move together in groups.
- Changes in direction: How often they turn while moving.
Puri tested ElSa using the BIRDSAI dataset, which contains thermal drone footage from four African national parks. According to the Davidson Institute, the system achieved 90.9% accuracy in detecting humans, approximately four times the accuracy reported for the comparison methods.
The results were encouraging, but ElSa has its limits. Just because the system detects a person in a wildlife area does not mean that person is a poacher. Rangers must still check the footage and investigate any unusual activity.
Why Did Anika Puri Build a $300 AI Wildlife Monitoring Tool?
Wildlife conservation teams often have limited budgets, and advanced monitoring equipment can be expensive. This makes it difficult for smaller teams to use modern technology to protect animals. Puri wanted to find a more affordable way to help rangers monitor wildlife areas. According to the Davidson Institute, high-resolution thermal cameras can cost around $4,800. Puri, however, developed her ElSa prototype using components worth approximately $300.
The lower cost makes her project particularly interesting for conservation teams that cannot afford expensive monitoring systems. ElSa could also save rangers valuable time. Instead of watching hours of drone recordings, they could use the system to identify footage containing detected human movement and focus on areas that may need investigation. However, the $300 cost covers only the prototype. Using ElSa in actual wildlife areas would require additional equipment, testing, and maintenance.
Why Is Anika Puri’s AI Innovation Important for Wildlife Conservation?
Protecting elephants and other endangered animals is a difficult job. Wildlife rangers often need to monitor large forests and national parks, where keeping track of every movement is nearly impossible. Anika Puri’s invention offers a possible way to make this work easier. By using AI to analyze thermal drone footage, ElSa could help rangers spot human activity more quickly and spend less time reviewing recordings.
Another important part of the project is its affordability. Many wildlife conservation teams cannot invest in expensive equipment, so a lower-cost tool could give them more options for monitoring protected areas. Still, ElSa is not a complete solution to poaching. The system can detect human movement, but it cannot determine whether someone is breaking the law. Rangers would need to investigate before taking further action.
With more testing and development, tools like ElSa could become a useful part of wildlife protection efforts.
Anika Puri’s ElSa project shows how a simple idea can grow into a promising wildlife conservation tool. Her AI system achieved encouraging results in detecting humans in thermal drone footage. With further development, affordable technology like ElSa could help rangers monitor protected areas and protect endangered animals.
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