ECE5990 Embedded Operating Systems: Final Projects

Our final project, the Embedded Phone, is to construct a basic phone with calling capabilities using the Raspberry Pi, a touchscreen, and a GSM module. The Embedded Phone will also be able to receive calls and translate messages from the GSM module to the touchscreen. As the main control unit, the Raspberry Pi will utilize PyGame and RPi.GPIO Python libraries to improve the user interface and front-end of the project.

In this project, we implement a self-learning digit recognition algorithm to determine the input given by a user using the piTFT touch interface. This project also explores the various techniques available to speed up the execution of the program.

The objective of this project was to design and create an encapsulated system that would use a camera to view the outside world and detect and recognize individual faces. This system would be contained in a single unit and could be carried around with any person.

The main objective of this project is to exploit the “IoT” potential of Raspberry Pi computer to control a Remote Car using the Voice Commands. The Raspberry Pi with a Microphone connected to it will receive the Voice Commands and will control the Remote Car by Processing the received Voice commands.

The main objective of this project is to build an embedded smart camera system by Raspberry-Pi. This embedded system can not only work as a camera but also as a video surveillance system. Moreover, the camera system provides additional image processing functions and the surveillance system is able to help save memory for storing video.

The aim of the project is to establish an understanding of speech recognition systems, both offline and online, as well as to develop applications on both systems. The goal of using an online speech recognition system, such as Google's speech recognition API, was for us to utilize a well-developed tool and expand it to create even more applications. The goal of implementing an offline speech recognition system was to create a mobile system that users can train to learn and adapt to their commands.

A smart home system is a mini loT network of people's personal in which all the electronic devices, including sensors of all kinds, household appliances and smart digital devices in a house are connected to each other and work cooperatively and automatically.

The objective of this project is to create a mobile robot platform powered by two servo motors. There is an onboard camera on the wiPiBot to give its pilot a view of the wiPiBot's sorroundings. The project utilizes a Raspberry Pi B2 model to command all the actions of the robot. Additionally, the Raspberry Pi hosts a server using the Django framework written in Python. The wiPiBot broadcasts the video and various data of its sorroundings to user, and the user controls the wiPiBot's motion through the dashboard that is hosted on the wiPiBot's server.

The goal of this project was to create a surveillance camera system for the Raspberry Pi. The Raspberry Pi enables the system to be very low-cost and lightweight, which allows for a simple way to surveil an area or an object. The system detects motion in the camera feed and will save video and still images to indicate any disturbances in the vicinity of the camera’s view.

The problem we mainly deal with is automatic balancing camera mount. Automatic balancing is very important for camera balancing, which is useful for aerial photography. As we know, it is very difficult for a drone keeping stable even with automatic pilot machine (APM), which reduces the performance of aerial photography. Automatic balance camera mount can enhance the performance and make stable aerial photography possible.

There are three main objectives during this project. First is to set up the Raspberry Pi cluster servers, the second is to install and configure the Hadoop specific for pi, the third is to run the Hadoop program in the cluster and compare its performance with regular java program.