Ideaz

In Hyderabad, our street dogs face a daily struggle for survival. Our current approach to their welfare is often a guessing game, driven by a lack of real data. We see the aggression, the suffering, and the overpopulation, but we've been tackling it with our hands tied.

Paw-Print is here to change that. We want to develop a small, smart device ,a motion-sensor camera attached to a humane gravity food and water feeder. We'll place them strategically in communities to capture crucial data on dog populations, their movements, and even their family lines with the help of local governments, NGOs and communities.

The Problem:

1. Lack of Accurate Data Regarding the population and other factors related to dogs
2. Inbreeding and Genetic Issues which are one of the main causes of aggression in stray dogs which go hand in hand with environmental factors
3. Without a clear understanding of population hotspots, migration routes, and dog-specific needs, existing animal welfare efforts are often a "shot in the dark," leading to waste and leaving countless dogs unassisted.

Our MVP Solution:

The "Paw-Print" Smart Feeder System Our MVP is a discreet, weatherproof device to be deployed in targeted localities. Each unit combines:

• Automated Food and Water Dispensing
• Motion-Sensor Camera which uses AI to track and detect the dogs and counts the population
• Geotags which helps in gathering the data at each data point and transmits it to our central database in real time.

Technical Information:

Our Device Contains :

Hardware components:

1. Camera: A low-power, high-resolution camera with an infrared (IR) night vision sensor to capture data 24/7. An IR filter is crucial for accurate daytime color and a clear night-time picture.
2. Processor: A NVIDIA Jetson Nano processor, chosen for its ability to run AI models on the edge, meaning data is processed locally before being sent, saving bandwidth and power.
3. Power Supply: Solar powered and rechargeable battery to store the power and use it during cloudy days
4. Gravity Feeder: Food and Water feeder which needs to be refilled by the volunteers over a period of time
5. Enclosure: A robust, tamper-proof, and waterproof casing to protect the electronics from the elements and from curious animals.

AI Components:

The core of this idea lies in the AI model's ability to identify individual dogs. This requires a multi-stage approach:

1. The first layer is Object detection model (YOLO orSSD) to detect and differentiate other things and animals from dogs
2. Reidentification Model is key layer to prevent recounting of the dogs. Thismodel will analyze the detected dog's image, focusing on unique features like fur color, patterns, size, and shape. It then generates a unique "feature vector" for that dog. When a new image of a dog is captured, the model compares its feature vector to all existing vectors in the database. If there's a match above a certain confidence threshold, it's identified as the same dog. If not, it's logged as a new dog.
3. Data Labeling of dogs. To train this model, we will need a large, labeled dataset of street dog images, a key challenge for this idea. To encounter this problem we can start with publicly available datasets and then collect and label our own data from the pilot project.

The data collected will be invaluable for:

• This Data is then used to create the appropriate number of shelters across the city where they are provided with basic amenities, health care and neutered when needed.
• Creating a real-time, high-density map of dog populations across the city, identifying hotspots and density changes, Breeding seasons for dogs , Movement and Migration tracking of the dogs and hierarchy structure of the dogs
• This Data will be used to create a Pedigree chart and Genetic analysis. Our AI will analyze unique markings, fur patterns, and other features to differentiate individual dogs, allowing us to track family lines and identify areas with high rates of inbreeding.

Conclusion:

This isn't just about counting dogs. It's about giving them a voice. The data we collect will allow us to see their struggles and needs with unprecedented clarity. By working with local government and community leaders, we will transform guesswork into a strategic, compassionate plan.

Paw-Print's mission is simple: to create a foundation of knowledge that will help us build a future where every street dog in Hyderabad is seen, cared for, and has a safe place to call home.