WIRELESS INTELLIGENT VIDEO SURVEILLANCE SYSTEM USING MOVING OBJECT RECOGNITION TECHNOLOGY

Abstract

This paper presents an innovative approach to cycle time reduction in internal quality management
through the implementation of an automated tool. The focus is on optimizing resource planning for productbased
organizations by analyzing variables such as resource numbers, request types, and testing methods.
Statistical modeling is utilized to enhance work allocation and provide precise status updates to development
leads, ultimately leading to significant cost savings and efficiency improvements.
The developed automation tool, as an alternative to manual test case testing, utilizes statistical modeling outputs
to assist in work allocation to members of testing team and also to collect the actual time spent on each of the
activities performed by them for further analysis. This will also help to provide correct status to development
leads. So that results can be communicated to development leads in advance whether their request can be met or
not. Resource planning is also required to do random testing in case there are few requests or quality of the
product is critical and this will help in identifying how much testing is done.
The next task after resources planning is server upload, which takes a lot of bandwidth of testing group to
upload the document and source code. Optimization of server based on understanding of upload sequencing and
server load. To meet the current load which will save several million dollars as the server cost is high.