title: Swiper No Mauling
start: 2019-02-01
end: 2019-02-01
project-url: https://github.com/prdlk/CV-Livestock-Protection
skills:
  - Python
  - TensorFlow
  - YOLOv3
  - Computer Vision
  - Machine Learning
  - Twilio API
description: |
  - Engineered a financially viable, AI-powered computer vision application designed to help farmers autonomously monitor livestock and prevent predator attacks.
  - Implemented the YOLOv3 object detection model using Python and TensorFlow to accurately identify predators and assess hostility levels within live camera frames.
  - Integrated the Twilio API to build an automated, real-time alert system that immediately dispatches SMS notifications to farmers the moment a threat is detected.
  - Designed an architectural roadmap to transition the computationally heavy detection model to a cloud-based infrastructure, with planned expansions for wildlife researchers to track events of interest.
associated-with: ../about/education.yml
evidence:
  - fact: "PennApps Spring 2019 submission per repo README; 99.6% Python; README confirms TensorFlow, YOLOv3, Twilio API stack"
    source: https://github.com/prdlk/CV-Livestock-Protection
    retrieved: 2026-07-03
  - fact: "Devpost submission to PennApps XIX (project started by Prad Nukala, 2019-02-03; 3-person team); built-with tags python, tensorflow, twilio, yolov3; includes YouTube demo"
    source: https://devpost.com/software/swiper-no-mauling
    retrieved: 2026-07-03