Students: He Li, Yuhao Chen, James Tay, Everett Berry, Yukun An, Jiaju Yue, Qingshuang Chen, Huanyi Guo, Daniel Dilger, Andrew GreenProfessors: Dr. Edward J. Delp, Dr. Yung-Hsiang Lu

Big DataThe ProblemCurrently there is no common computing infrastructure which can support continuous analysis of many internet connected cameras and so researchers are unable to harness this vast amount of data for analysis.

The Infrastructure1. A large number of publicly available cameras and their properties2. A set of functions common to different analysis programs and an API for developing

the analysis programs3. A resource manager (system) which optimizes the resources needed for running the

analysis programs

Possible ApplicationsUses of the system include:• Traffic analysis to improve congestion or detect accidents• Weather observation to increase the accuracy of existing weather models• Environmental trends (rising sea levels, shorter days, etc.)

System Team Progress• System rewritten in Java from Python to take advantage

of:1. Better data structures2. Java Virtual Machine (compile on any

machine)3. Large standard library4. Pure object oriented scheme

• Database converted to MySQL from XML files for easier data management

• System redesigned to handle a more diverse set of applications

• Locations of cameras found so far mapped (below)

Cloud-Based Distributed System ArchitectureAbove is a lower level view of the interactions of the distributed system from application upload to the job scheduler. Two monitors provide information about the performance of the system and the data flow during operation. A database holds everything from logins for the website to reports generated automatically by the manager.

Image Processing APIThe image processing API is designed for image processing algorithm testers to use our system easily. All they need to do is just write a pure processing algorithm and plug it into the API.

Tasks for the API1. Download images for cameras and store them into a buffer.2. Send Reports to the system.3. Run the image processing algorithm.

Future DevelopmentShort Term:• Test Java implementation of system• Scale up from 7 worker computers and 200 cameras to

hundreds of workers and thousands of cameras• Build API which will interface with a website• Improve rain detection and sunrise/sunset algorithmLong Term:• Scale up to millions of cameras and thousands of workers• Upgrade to billable system• Develop 4 or 5 weather detection algorithms

Rain Detection algorithmThis algorithm analyzes videos from cameras and detect if it is raining.

Fig.6 Weight of Rain

Fig.2 CloudyFig.3 Rain

Fig4 weight of sunny Fig.5 Weight of cloudy

Fig.1 Sunny

Sunrise/Sunset DetectionThis algorithm analyzes videos from cameras and detect if it is sun rising or sun setting. From the result retrieved, the length of the day can be calculated.

Steps1. Detect Horizon2. Calculate brightness of sky using pixels above horizon3. Store value and repeat4. Sudden increase in brightness in morning may indicate sunrise.5. Sudden decrease in brightness in evening may indicate sunset.

Time: 20:42 RGB Avg: 52Time: 20:39 RGB Avg: 71Time: 20:31 RGB Avg: 111

sunset

Rain Detection results