公司规模
Large Corporate
地区
- Europe
国家
- United Kingdom
产品
- Kaba 20 system
技术栈
- Automatic locking and unlocking device
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
技术
- 功能应用 - 远程监控系统
适用行业
- 铁路与地铁
适用功能
- 物流运输
用例
- 远程控制
服务
- 系统集成
关于客户
First Great Western 是英国一家大型列车运营商。他们在前 Wessex Trains、First Great Western Link 和 First Great Western 路线上运营高速、通勤、区域和支线列车服务。他们的愿景是为客户和社区提供安全、可靠和愉快的旅行。他们致力于改善服务并确保乘客安全,这就是为什么他们寻求解决方案来应对确保乘客在较短站台下车时安全的挑战。
挑战
First Great Western 运营高速、通勤、区域和支线列车服务,服务范围覆盖前 Wessex Trains、First Great Western Link 和 First Great Western 线路。他们的愿景是为客户和社区提供安全、可靠和愉快的旅行。然而,他们在确保乘客在较短的站台下车时的安全方面面临挑战。他们需要一种用于高速列车的选择性开启装置,以便列车经理控制列车门的自动锁定和解锁装置。
解决方案
dormakaba 能够以 Kaba 20 系统的形式提供解决方案。该系统允许列车管理员控制列车门的自动锁定和解锁装置。列车管理员可以站在站台末端的最后一节车厢,只需将他们的 Kaba 钥匙插入 Kaba 钥匙开关,他们就可以防止站台外的车厢门与列车其余部分一起自动解锁。Kaba 20 系统由独特的光滑 Kaba 凹窝钥匙操作,坚固耐用、可逆,拥有超过 1 亿个钥匙代码。dormakaba 开关锁可以与其他产品(如凸轮锁、门锁和挂锁)一起包含在 Master Keyed 系统中,以提供高水平的组织控制,用户只需携带一把钥匙即可。
运营影响
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Building Smart IoT-Connected Railways
• Difficult environment. Communications equipment on trains must function properly in harsh conditions, such as environment temperatures ranging from -25°C to +85°C, according to the EU standard EN50155.• Railway regulations. All products in a train must adhere to strict standards, relating to working vibration, power consumption, and lifetime.• Lengthy process. Time to market in the railway industry can take years from concept to mass production, so product design requires a solid long term vision.
Case Study
Connected Transportation: A Smarter Brain for Your Train with Intel
A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.
Case Study
Using LonWorks to Keep Acela Trains Zip Along
Canadian transportation company, Bombardier was tasked with building a bullet train system on rails that were designed for lower speed trains. In addition, they had to ensure safe and optimal operation at high speeds, maximize train uptime and enhance communication with passengers.
Case Study
Delhi NCR Metro: A Mobile App Revolutionizing Public Transportation
The Delhi NCR Metro, a major public transportation system in India, was facing a challenge in providing accurate and comprehensive information to its daily commuters and tourists. The lack of a centralized platform for information about metro station details, train schedules, fare details, parking, elevators, and tourist locations was causing inconvenience to the users. The challenge was to develop a mobile app that could provide all this information accurately and conveniently. The app needed to be equipped with GPS services to help users find the nearest metro and renowned locations. An interactive map was also required to assist travelers who were familiar with the metro lines. The goal was to provide maximum information with minimum input.
Case Study
Automated Railcar Inspections Increase Security and Revenue
Providing industry and government customers with intelligent inspection, automation, safety, and security solutions, Duos Technologies Group, Inc. (“Duos” or the “Company” - Nasdaq: DUOT) continually pushes the boundaries of IT. To keep pace with expanding AI-enabled data capture analytics for its edge railcar inspections, the company chose the latest Dell EMC PowerEdge servers.Duos Technologies’ challenge was finding a way to leverage technology as a force multiplier to meet customer requirements for a better, faster inspection process for trains running at full speed. Duos developed innovative data analytic solutions with AI at the edge to conduct more reliable railcar inspections, which are available 24/7/365 in all climates and conditions.