Ipilot is an AI program which will help motorists within Nairobi to navigate through the nasty traffic jam they experience everyday.

Artificial Intelligence

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Ipilot uses memory-argumented neural network known as differentiable neural computer to help motorists navigate through the nasty traffic jam to their destination. Since differentiable neural computer (DNC) is a model developed by google DeepMind I want to apply it to solve the only major issue we experience everyday in our capital. We waste Ksh. 2 billions every year on traffic jams. Why don't we channel those funds to help the food issue on dry parts of the country and also address the water shortage issue. Ipilot will use a graph traversal algorithm then pass it to DNC algorithm and find the best and shortest path to your destination. In the DNC the graph generated from our graph traversal algorithm will be subject to an Natural Language Processing (NLP) process condition which it will view peoples opinion on the graph generated and output the best graph based on peoples opinion, also it will factor out a way to avoid assigning too many motorists in a road to avoid another traffic jam.

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Rima M. updated status

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Rima Modak

I am currently working to develop a prototype of an device based on IoT. This device will be used to detect any kind of material. It will be used to detect both living and non-living things, and after detecting, it will display varies other things related to the detected object according to the tags provided by the user/customer.

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Aravindhan N. created project Automatic attendance management system using face detection

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Automatic attendance management system using face detection

Automatic attendance management system will replace the manual method, which takes a lot of time and is difficult to maintain.There are many bio metric processes ,in that face recognition is the best method. In our campus staff attendance is taken with the help of Gesture recognition /attendance sheet .We can take this to next level by implementing Artificial Intelligence based Face Recognition using Convolution Neural Network(CNN). We have to train our neural net using COCO (large Image dataset designed for object detection) and Staff Dataset (Several images of individual staffs). Since we don't have the photos of the staffs,we have trained our neural net using our own photos.Our Neural net consists of 20 neurons in the hidden layer which help us to diagnose the pixels of the image and compares the result with the trained dataset .By using our advanced system the staffs can use their own mobile/laptop [camera] for registering their presence in their own place which is possible only if they are connected to our college Network (WiFi).

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