The event held on the 1st of December 2022 at the site of the newly built AI studio. It had in display a dozen different projects that were using Artificial Intelligence to solve real life problems in the community ranging from security, agriculture e.t.c. Most importantly the progress on the ngDroneNet was displayed to the public via the Automatic Landing and Recharge system. The goals of the OAU AIR Fair were to inform and to inspire. With respect to the first goal, the exhibition will provide an opportunity for research groups to exhibit ongoing projects in which AI is being used to solve real-life problems.
The AIR Fair was to provide a vehicle to inform members of the community about ongoing AI-related research like the ngDroneNet and related ones. The event organizers hope that this will in turn inspire even more researchers and students to apply AI in their work, since AI remains a relatively fertile ground on which Nigeria can plant the seeds of a vision to reach the forefront of the global technology space.
The exhibition coincided with the commissioning of the Alumni AI Studio of the Department of Electronic and Electrical Engineering. The Studio is the brainchild of the Applied Artificial Intelligence and Robotics Research group of the department. This was occasioned by the fact that due to severe space constraints, the department has hitherto been unable to provide her students with a befitting workspace within which to conduct AI-related research. This has greatly limited such student and research assistants. An idea was pitched to some alumni and partners of the department to create a model workspace to address this problem. The goal of the AI Studio is to allow selected students to work in an environment somewhat similar to what obtains in North American universities. Free Internet access and 24/7 electricity are guaranteed to students working in the Studio. Furthermore, an increasing number of them will be placed on stipends to ease financial pressures. Teleconferencing facilities have also been put in place so that alumni can directly call in and interact with Studio students from time to time through a 60-inch LED screen. Maker facilities such as a 3D printer are already in place, as is a workstation with two Nvidia RTX 8000 Quadro graphical processing units, capable of over 260 TFLOPS of machine learning performance, graciously donated by NVIDIA Corporation of Santa Clara, California
The external and internal view of the studio is given below with the state of equipping is shown below

The Department hopes that the Studio can serve as a proof of concept, and that other alumni and partners will help fund the creation of even more workspaces and complementary initiatives. Already, a group of alumni have announced a complementary Innovation Prize competition with cash prizes totaling seven million naira per year. The current studio has a capacity of 20 students, which is a small fraction of the total student population of 700, making even more workspaces a key need. According to a spokesperson, the Studio also needs additional support to provide a solar-powered energy backup system, to replace the current petrol generator, which is noisy and not environmentally-friendly.
The list of exhibits during the tech fair is given below
⦁ PULSR | Platform for Upper Limb Stroke Rehabilitation is a rehabilitation robot for improving functional outcomes for patients who have motor function impairments due to stroke.
⦁ PULSR 3 | Third generation of the PULSR robot which seeks to integrate electroencephalography to allow much earlier commencement of robot-mediated therapy after stroke.
⦁ Generis | A system using mismatch negativity and electroencephalography-derived measures for quick, accurate and reliable measurements in the management of schizophrenia
⦁ SSVEP Demonstrator | A project using steady state visually evoked potentials to detect arm and leg movement simply by acquiring signals from subjects’ brains
⦁ Physiora | Pose estimation and federated learning for mobile device-based remote monitoring of, and feedback to patients as they carry out rehabilitation exercises at home
⦁ Drones for plant health monitoring | In this project, the number of crops along a drone’s flight path across a large farm are automatically counted, with images also stored for further assessment by the farmer.
⦁ Plant Disease Identification Using Deep Learning | Convolutional neural networks for automatic disease detection in crops such as maize, cassava, potatoes, and pepper.

⦁ Robotic Orthosis for Hand Rehabilitation after Stroke | The project uses brain-computer interfacing and machine learning to help subjects move their fingers as they attempt to regain motor function after stroke.
⦁ ngDroneNet | Instrumentation, control and artificial intelligence for automatic landing, recharging and object detection in a network of low-cost quadcopters, facilitating situational awareness capabilities for many applications
⦁ WeatherWAN | Proof of concept for a country-wide IoT network of weather stations, using a low-cost, high-reliability design that is rugged enough to work in all parts of Nigeria with minimal maintenance requirements.
⦁ RoadMapr | RoadMapr aims to make use of the millions of accelerometers in the mobile phones of road users to provide real-time information about the surface conditions of various portions of the road.
⦁ Percussogram | A medical device employing convolutional neural networks to automate medical percussion