Intelligent Distributed Mobile Computing-OS Technology
20150330 - 20160929
Dr Xiaohua Wu
1. Software engines with the following technologies: a) Image enhancement, reconstruction and fusion algorithms b) Middleware level sensor fusion and context-aware intelligence using embedded distributed machine learning technology with compatible Android API c) Robust “Low Latency Scheduler” at Linux kernel level d) Latency is about (20~30ms) 2. Reference design of demo applications for business engagements a) “Wearable Camera” and “Gaming/VR HMD” applications with above software engines. 3. Deliverables for Customer 1: a: Documentation of algorithms with UAT case and application programming interface (API)* b: Prototype software module with Image Enhancement as defined in item 1 of Schedule 3 (in C source code) (Refer to Ref: CR1409-002) c: Prototype software module with Image Reconstruction and Image Fusion capabilities as defined in items 2 and 3 of Schedule 3 with streamer application (in C source code) (Refer to Ref: CR1409-002) d: Optimized software modules of Item 2 & 3 for final release package. Refer to Ref: CR1409-002. *Here API means API for Image Enhancement, Reconstruction and Fusion.
Mr Yee Lim Chan Ms Lu Wang Ms Yee Wai Mandy Yim Mr Hanqiang Huang Mr Pan Lit Wong Mr Chi Chung Leung Ms Hua Yang Mr Fu Chun Li Mr Kwok Hung Leung Mr Yat Cheung Ngai Ms Yin Yee Chan Mr Ka Yuk Lee Mr Chun Chung Lo Mr Tony Wu Mr Sai Hung Chu Mr Rihong Chen Mr Cheung Ming Lai Dr XiaoHua Wu Mr LaiFa Fang Mr Sai Fan Chan Mr QiangQi Zou Mr Wai Lun Lee Mr Ching Lun Lo Mr Fu Tuen Leung Mr Ding Lap Cheung Mr Chi Hing Chau
Aircraft Medical Ltd [Sponsor] Clever Motion Technology Ltd (Cash) [Sponsor] Clever Motion Technology Ltd (TL) [Sponsor] HK JiuLing Technology Co., Limited (CS) [Sponsor] KoolSee Medianet Corp Limited (Cash) [Sponsor] KoolSee Medianet Corp Limited (TL) [Sponsor]
Wearable and Ubiquitous Computing has become the next major wave of technology and market trend after Mobile Internet Computing, since the Post-PC Era. Most of the industry players are focusing on the hardware sensing technologies. The overall system and operation software aspects are still in the early stage. This project aims to develop a Linux/Android OS and middleware to distribute tasks among wearable devices and smart phone/tablet for sensing data collection, intuitive user interaction and processing-intensive machine learning intelligence. The technology will be hardware- and Android-version independent, to support ASTRI’s sensor technologies and 3rd party off-the-shelf hardware components. Unified APIs are provided for third party application developers to utilize fused sensing data and machine learning engine for developing innovative applications. Reference design of a high-efficiency embedded distributed mobile computing system using the above software technologies will be developed. Demo applications, a low-latency position tracking and streaming “Head-Mounted-Display” for virtual reality and gaming applications, and a wearable camera for surveillance applications, will be developed using the above platform technology for proof-of-technology, innovative applications/business opportunity, and early commercialization engagement purposes.