Instructor: Dr. Hanna A. Kirolous RFID Automated Library Management System

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1 Instructor: Dr. Hanna A. Kirolous RFID Automated Library Management System Radio Frequency Identification (RFID) is a new generation of Auto Identification and Data collection technology which helps to automate business processes and allows identification of large number of tagged objects like books, using radio waves. RFID based Library Management system (LMS) would allow fast transaction flow for the library and will prove immediate and long-term benefits to library in traceability and security. In the proposed system, the students will design and implement microcontroller system based on UHF RFID readers, supported with antennas at gate and transaction sections. The library cards containing RFIDtransponders which are able to electronically store information that can be read the stored data even without the physical contact with the help of radio medium.

2 Instructor: Dr. Omar Ahmed Nasr Send with title (Graduation Project CHS) with your CVs and the project you are interested in if you would like to apply for a project. 1 st Project: Kids tracking Identifying people can help in many applications and tracking them can help in many applications. One application is tracking kids in crowded areas. For example, in a mall, kids usually play around and they can lose contact to their parents. The objective of this project is to develop a system that uses cameras installed in different places in a certain building (e.g. a mall) to track the kids from the time they enter this place until they leave. A video of the kid can be transferred to his parents and an alarm can be send to his parents if the kid left the safe area. This should be done in real time with no delay This project will involve the following tasks: 1- Installing cameras in a certain area in a way to fully cover the place 2- Reading the video streams from the cameras 3- Processing the stream to detect the number of people in the video scene 4- Identifying the kids in the scene 5- Tracking the kids in every camera view and determining their places [this involves people recognition and tracking] 6- Sending a video stream to the parents 7- Sending an alarm if the kid left the safe zone Tools: video processing, camera interfacing, Android programming, GPU programming, machine learning 2 nd Project: Smart Droplet v3.0 We have developed a node called Droplet two years ago that can replace the access points at homes. The main difference between our Droplet and the normal access point is programmability. Users can easily interact with this Droplet. The Droplet is based on Raspberry Pi platform. To show its capabilities, we have developed a mobile application that can interact with the Droplet at home. The user, when he is outside his home, can choose a video to download from youtube or other sites. The user, through the mobile app, sends the web link to the Droplet

3 at home. The Droplet downloads the video until the user comes back home, then the user can watch it either on his laptop, mobile or tablet through a wireless local network. This is an implementation to what's currently called video caching. This reduces the buffering time when users watch the videos when they return back home, and this also reduces the load on the network. Last year the students developed a distrusted social network based on the Droplet. Each user hosts his/her data on his personal Droplet. In the famous social networks, like facebook, the data is stored in servers owned and managed by the company itself. Facebook and other technology giants usually get many revenue streams from selling the customers data to advertisers, which puts the privacy of the customer at risk. The students have also developed some other applications for the Droplet In this year, it is required to develop more advanced features for the Droplet. Three main features should be added: (1) network coding based on Droplet. This will be used to further secure the users data. And (2) video caching over 3G/4G networks, (3) adding touch screen and building a good user interface for the Droplet. Tools required: python programming, networking, embedded systems and interfacing

4 Instructor: Dr. Mohamed Refky IOT transceiver The general idea of this project is to design and fabricate a full transceiver (transmitter and receiver) that is suitable for IOT (internet of things) applications. Low-energy Bluetooth transceiver will be the main target of this project. Version 5 of Bluetooth standard (the newest Bluetooth standard) with four times the range of its predecessors and double the transmission speed can send and receive data more quickly and this makes it suitable to be widely used in 5g IOT applications. This standard operates in the 2.4 GHz ISM (Industrial Scientific Medical) band. This project has many useful applications including blood pressure monitors, industrial monitoring sensors, public transportation apps.

5 Project 1: Biomedical Signal Processing Instructor: Dr. Hassan Mostafa Graduation Projects Proposals 2018 Research Projects -This project includes providing the Matlab and HDL implementation for the algorithms used in the detection and prediction of the neural brain signal and sending back an electric stimuli to treat the seizure (for Epilepsy and Parkinson). The project aims at using machine learning techniques to do the detection and prediction with low power emphasize. One of the candidates is the Support Vector Machine (SVM). -The outcome of this project is a working FPGA prototype as well as an ASIC tape-out for fabrication. -FPGA Programming, ISE, VHDL/VERILOG, MATLAB, CADENCE, CALIBRE, ASIC flow, and FPGA flow Project 2: SDR Implementation -This project includes the implementation of the Software Defined Radio on the FPGA (ZYNQ Board). The standards to be adopted are: 2G, 3G, LTE, WiFi, and Bluetooth. Only the Bluetooth is missing and some other power optimization are needed. -The outcome of this project is a working FPGA prototype. -FPGA Programming, ISE, VHDL/VERILOG, MATLAB, FPGA Flow Project 3: Neuromorphic (Brain Inspired) Computing -This project includes the implementation of the low power hardware required for the neuromorphic (brain inspired) computing. This project aims at developing the required hardware for machine learning such as robots and autonomous car to give them the ability to take fast decisions similar to the human brain. -The outcome of this project is a working FPGA prototype as well as an ASIC tape-out for fabrication. -FPGA Programming, ISE, VHDL/VERILOG, MATLAB, CADENCE, CALIBRE, ASIC flow, FPGA flow

6 Instructor: Dr. Ahmed Khattab Machine Learning for Medical Applications Within the field of data analytics, machine learning (ML) is a method used to develop algorithms that predicts trends in the available data. This is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data. With the outbreak of the Internet of Things (IoT) and the availability of huge amounts of data that is collected on a 24/7 basis, ML is becoming of a paramount importance to flourish the gains of IoT. In this project, you will learn the basics of ML and apply them to real-life data. The goals of this project are: Learning the basics of ML. Write ML Algorithms from Scratch. Comparing the performance of different ML Algorithms on real datasets. Proposing a new ML approach (Bonus) Required skills: Willingness to learn Outstanding programming skills Good teamwork skills Self-motivation Minimum Grade: B

7 Instructor: Dr. Amin Nassar Phone number Energy Management for Home Appliances Brief: Management system that monitors and controls the power consumption of home appliances.