Students use advanced Data logging mechanisms to extract sensor data from the Lidar 360 degree Laser Scanner, Vision Cameras, Sensors, and the Navigation System on board a fully autonomous retro fitted Renault Twizzy road car. They also learn about Localization, Mapping, and self driving strategies and Safety System. Students will analyze the data and create simple self-driving algorithms using machine learning and computer vision models. Having support from Al Tamimi, the region’s largest law firm, students will also learn about how governments can form laws around self driving cars.

EMOTIV’s Mental Commands algorithm recognizes trained thoughts that can be assigned to control virtual and real objects just by thinking. DAA AI Students are exploring how Brain control can replace traditional input devices like keyboards and buttons, to enhance interactive experiences and provide new ways for people of determination to engage with their surroundings.

The Baxter Research robot is used to support numerous research and education programs such as human-robot interaction, collaborative robotics, planning, object recognition and object manipulation, computer science, perception, neurosciences, and cognitive sciences. At DAA, we have students working on industrial level ROS or Robot Operating System and python programming to teach Baxter to learn faces and make delicious coffee based on user preference.

Using state of the art VR headsets and VR treadmill systems, students have the power to experience VR like never before. They also create Virtual , Augmented and Mixed Reality experiences using UNITY software and other 360 developmental platforms. This gives them the opportunity to be Creators, rather than just consumers of VR content. Using Engage and similar apps to host VR training sessions and collaborative simulation experiences, and apps like Google Tilt brush to create Art and 3D surroundings, including importing of their 3D models using Google Poly, just takes their immersive VR experience to the next level.

FarmBot is an open source precision agriculture CNC farming project consisting of a Cartesian coordinate robot farming machine, software and documentation including a farming data repository. The project aims to "Create an open and accessible technology aiding everyone to grow food and to grow food for everyone." Students here at DAA learn the concept of desktop Drag and Drop farming and use MAchine Learning Algorithms to make better decisions to grow a better, healthier and fuller yield of crops. RIght inside the Lab.