28 June 2021 to 2 July 2021
Europe/Vienna timezone

AI Enabled System for OSI IT/ISP Living/Working Area Management

P3.6-096
1 Jul 2021, 09:00
3h
Online

Online

e-Poster T3.6 - Artificial Intelligence and Machine Learning T3.6 e-poster session

Speaker

Mr Peng Li (Hope investment Development Corp. Ltd., Beijing, China)

Description

According to OSI Operation Manual, IT/ISP living and working areas should be well-protected. Scenarios like the management of the different living and working areas for IT and ISP, require entry permission granted separately to either IT or ISP members. This work would provide a customized management supporting system solution to the above mentioned scenario. The system is based on Artificial Intelligence (AI) related hardware learning and self-deep learning. System functionality involves personnel detection, image classification and recognition. The whole system combines thermal, daylight/CCTV and laser lighting/range-finding with application software. It also supports dynamic and static targets detection and recognition including human, animal, vehicle, smoke, fire and high-temperature items, with AI functions of detection, recognition, classifications, and reactions like alarm, denied access. IT/ISP members’ image could be pre-loaded into the system, which would grant permission to IT/ISP individuals or deny their access. The system could be compatible with OSI IIMS and other third-party systems. The system also supports area intrusion/leave/behavior analysis. In order to achieve high level image recognition, the deep-learning software could work under harsh environment by intelligence function such as defog, background analysis and area shield. Individual privacy issues would be jointly and legally solved together with the PTS.

Promotional text

This work carried out a system solution to OSI IT/ISP living and working areas management supporting system, based on Artificial Intelligence (AI) related hardware learning and self-deep learning.

Primary author

Mr Peng Li (Hope investment Development Corp. Ltd., Beijing, China)

Co-authors

Mr Zhen Wang (Hope investment Development Corp. Ltd., Beijing, China) Mr Libin Niu (Hope investment Development Corp. Ltd., Beijing, China) Mr Jing Yang (Hope investment Development Corp. Ltd., Beijing, China) Mr Xinmin He (Hope investment Development Corp. Ltd., Beijing, China) Mr Yuan He (Hope investment Development Corp. Ltd., Beijing, China)

Presentation materials