IATI MNC 3rd Weekathon Demoday: The PresentationsMar. 29, 2015
1. Autonomous quadcopter for police chases - a product which uses computer vision algorithms and a dedicated software we developed in order to autonomously identify and track suspects. For the product's videos click here.
Developers: Ben Dayan (GE), Sasha Glazman (Marvell), Igor Burshteyn (Kodak), Jacob Shem-Tov (Motorola), Adir Amsalem (citi).
2. Green Light Wave: Traffic Control System - an emergancy vehicle time optimization system. The system uses predicted driving path and real time vehicle location, and so prioritizes traffic lights behavior in favor of emergency vehicles such as police car and ambulance.
Developers: Shay Avivi (Motorola), Liron Netzer (citi), Yossi Gabay (Marvell), Konstantin Taran (GE), and Roman Morgenstern.
3. MP-TCAS: Mobile Phone Traffic Collision Avidance System - a smarthphone based proximity identification system. The solution is based on Mobile Phone (MP) sensors only (Pressure sensor, Gravity sensor and the GPS module) and the concept can be applied on a few relevant domains (automotive, aviation, shipping, drones). For the Weekathon, the developers have focused on applying the concept on General Aviation and the light sport aircrafts categories. The product was tried out on the customer's site - Hertzliya Airfield, the center of the general aviation activity in Israel. The results can be seen on this video.
Developers: Guy kahlon (citi), Guy Banay (Kodak), Gabi Ofir (Motorola), Shahar Fattal (Marvell), and Haim Kahlon (Motorola).
4. SitApp: Workout Chair - an office chair that will correct the sitter's sitting stature, allow freer movement and will remind about doing some excercise once an hour, in order to keep the back straight, the muscles moving and the blood flowing.
Developers: Roey Fizichky (Motorola), Yael Levy (Marvell), Oren Glickman (citi), Kobi Goldstein (Kodak), Ori Gutman (citi).
5. ALS patients monitoring and analysis system - The project goals were to introduce new ways for motoric data collection: Rough motoric data collection, Using IMU sensors located on the smartphone and the body/clothes. The wearable sensors are connected wirelessly (BLE) to the patient smartphone` they are stored in the cloud for analysis and research, and there is a Web UI for patient data visualisation.
Developers: Lilach Tesler (citi), Moshe Taieb (Kodak), Hezi Shahmoon (Marvell), Igor Shishkin (Kodak).
For more info on IATI's MNC 3rd Weekathon click here.