Sunday 10 a.m.–1 p.m. in Expo Hall
The Forest Fire Alarm System Using Drones and TensorFlow Python
The Drones also known as Unmanned Aerial Vehicles (UAVs), or Unmanned Aerial Systems (UASs) are growing rapidly over the past few years and are expected to keep growing in the very near future. The drone market is expanding with new models that target different segments of the consumer and commercial market, such as wildfire alarm system, climate change, aiding in wildlife preservation, improving agricultural management, insurance adjustment, real estate surveying, automated deliveries, roof inspections, tracking disease outbreaks, and directing disaster relief. Also, when the drones are combined with a super machine, high-definition cameras, smart sensors and devices, cloud AI resources, and other new technologies, the drones become remarkably more advanced. However, this proposal presents the Forest Fire Alarm System that will be used to connect a drone to the IBM Watson cloud for detecting and alerting the Fire Department about smoke, fire or other emergencies. The Forest Fire Alarm System has two main models. The first model is a drone model that uses machine learning algorithms using python TensorFlow and OpenCV with some machine learning libraries. This model runs on a drone that has AeroBoard with Nvidia Jetson TX2, a high-definition camera, Forward-looking infrared (FLIR) camera, smoke detector sensor, professional microphone, and LTE/4G modem. The second model is a cloud model that runs on the IBM Watson cloud with some IBM APIs such as visual recognition, Internet of things, data analysis and other tools. The main aim of this proposal is to build a drone that can fly by itself using autonomous fleet management. When the drone is in the sky and starting its mission, the drone model will analyze and gatherer the videos, voices and data in real-time from the forest by using python TensorFlow and OpenCV with some machine learning libraries, then extracts frames of the videos that collect by the cameras, the feature of voices that collect by the microphone, and the data that collect by the sensors; then the drone model will send all frames, features and data to the cloud model in the IBM Watson cloud server for analyzing all them, and making the final decision, then sending the result to the Fire Department dashboard.