Alagan Anpalagan
Embedded Systems
Integrated NotifyMe System is a web and mobile application which allows users to check the travel and wait times at various places such as highways, subways, theme parks. By periodically analyzing live video feeds of lineups, social media information and crowdsourced data, and using data processing and machine learning algorithms, NotifyMe is able to estimate overall travel/wait time in real time. It will be done in a single integrated system that involves multiple locations and updates at different times. This allows users to make an informed decision to choose a desired option after analysing different available options presented by the system.
The overall goal is to design, develop, implement and test an integrated end-to-end system that calculates the overall time to get from point A to point B that involves multiple routes and locations. Different kind of data will be collected and analyzed to make a decision accurately as possible using data processing and machine learning techniques. It should be done cost effective manner possible without compromising the quality of the product and services to be provided by the system.
The partial specs listed below:
* The Integrated NotifyMe System to be implemented should: (a) use of web and mobile application involving software and hardware such as Arduino (or appropriate) board in sensing, data acquisition, and networking and (b) in real- time data collection from video feeds from cameras, twitter feeds and possibly crowdsourced data available in a webAPP, (c) use Python or Java/C++, and Android/iPhone-based display, (d) demonstrate efficiency in automated operations for end users (accurately estimated travel/wait times). This project may be done with the combination of simulation and real implementation.
- Research on different modules required for the project (software or hardware, sensing, communication and processing)
- Study the literature/technical papers on data acquisition and fusion, cameras and sensors for live data
- Study machine learning techniques for automated decision making involving multiple inputs with different reliable levels
- Design a data acquisition systems (using cameras, sensors, social media as appropriate) and develop software/server for the data acquisition/processing
- Incorporate intelligent decision making using machine learning technology to fuse different data to calculate the overall travel+wait time, and provide multiple options to users to choose from
- Use modular approach in design/test and then integrate.
- Design/develop the GUI with appropriate inputs and ease of use
- Arduino (or similar) programming and APPS development for demonstration
- Test the integrated system for typical/extreme utility conditions which will be done through simulation and some implementation.
To design, develop, implement and test an integrated web and mobile application that calculates the estimated travel time in real-time.
To design, develop, implement and test an integrated web and mobile application that calculates the estimated travel time in real-time.
To design, develop, implement and test an integrated web and mobile application that calculates the estimated travel time in real-time.
To design, develop, implement and test an integrated web and mobile application that calculates the estimated travel time in real-time.
To design, develop, implement and test an integrated web and mobile application that calculates the estimated travel time in real-time.
AA09: Integrated NotifyMe System | Alagan Anpalagan | Tuesday September 7th 2021 at 06:42 PM