Trespasser Identification and Deterrent System (TIDS)

锆石软件在铁路行业内开发高完整性安全相关应用方面拥有丰富的经验。我们对在每个RIRL中为Knorr-Bremse、西门子和Petards等知名组织的产品部署提供帮助的理解将是我们成功的关键。此外，Zircon在处理复杂的硬件和许多专门为铁路设计的COTS(商业现成)产品方面拥有经验，我们的知识还包括支持网络上的现有运营系统。锆石参与机器学习(ML)研究已超过5年。特别值得一提的是，许多研究利用了视频分析。经过6个月的成功试验，之前的一个名为站台列车接口(PTI)凸轮的研究项目被安装在伦敦地下维多利亚站。PTI Cam检测到乘客从站台到轨道的相互作用和入侵。PTI凸轮是建立SEBS解决方案的基础。PTI Cam提供了一个成功的演示。锆石在这场比赛中也采取了同样的方法，并将其应用到概述的场景中，特别是：非法侵入(走捷径、逃票、涂鸦)和盗窃。该系统可能不可避免地检测到潜在的自杀企图，这不是它的预期目的，尽管可能被视为次要用例。TIDS是模块化的独立离网闭路电视安全系统，能够部署在所有环境中，旨在阻止非法侵入铁路网。该系统是完全自动化的，利用统计分析和机器学习算法，其中一部分已经在过去的项目中得到验证。通过部署TID等自动强大的威慑设备，我们将减少因非法侵入而导致的列车延误数量，这将对提高客户满意度产生直接影响。

Zircon software has a wealth of experience in developing high-integrity safety related applications within the rail industry. Our understanding of assisting clients throughout each individual RIRL's up to product deployment for well-known organisations such as Knorr-Bremse, Siemens and Petards will be key to our success. In addition, Zircon has experience in working with complex hardware and a number of COTS (Commercial Off-The-Shelf) products specifically designed for rail while our knowledge also covers supporting existing operational systems on the network. Zircon has been involved in Machine Learning (ML) research for over 5 years. In particular much of the research has utilised Video Analytics. After a successful 6 month trial, a previous research project called Platform Train Interface (PTI) Cam, was installed at London Undergound Victoria station. PTI Cam detected passenger interaction and intrusion from platform to the track. PTI Cam forms the basis upon which the SEBS solution can be built. PTI Cam delivered a successful demonstration. Zircon are taking the same approach in this competition and applying it to the scenarios outlined, notably: trespass (short-cuts, fare evasion, grafitti) and theft. The system may inevitably detect potential suicide attempts which is not it's intended purpose, although could be seen as a seen as a secondary use case. TIDS is modular stand-alone off-grid CCTV safety system capable of being deployed in all enviroments and designed to deter trespassers on the railway network. The system is fully automated utilising statistical analysis and machine learning algorithms, parts of which, already proven in past projects. By deploying an automated powerful deterrent device such as TIDs, we will reduce the number of train delays as a result of trespass which will have a direct impact on improving customer satisfaction.