Objective
To meet environmental and economic pressures for increased use of public transport, metro operators need to develop efficient management systems for their networks. The ADVISOR system addresses these issues by exploring advances in computer vision technologies and open network architectures to demonstrate effective use of CCTV for computer-assisted automatic incident detection, content based annotation of video recordings, behaviour pattern analysis of crowds and individuals, and ergonomic human computer interfaces. System performance targets will be developed by a user group and refined by three demonstrations of increased functionality. The measurable benefits will be reduced operator workload, faster response to incidents, more efficient management and retrieval of video data and improved means for analysing public use of transport systems. Specification and procurement of systems will be facilitated by the open architecture adopted.
Objectives:
The strong political drive within Europe to encourage use of public transport will lead to increased passenger flows through metro stations and other critical elements of the public transport infrastructure. To meet this demand, public transport operators must improve the efficiency and security of their operations. The use of computer vision techniques will enhance the role of CCTV in meeting these objectives. The ADVISOR system builds on recent advances in computer technology applied to CCTV, academic research into computer vision and, in particular, progress made in recent European funded programmes. The system will provide a set of decision support tools, which will enhance the value of CCTV as an asset for managing public transport operations. The operators are interested in reducing the workload on network controllers by automatically alerting them to situations requiring attention, and in increasing the utility of information from the cameras by annotating the images according to their content. They will benefit from the adoption of a set of open standards to facilitate specification, procurement and testing of advanced CCTV systems.
Work description:
The results of previous work in this area will be used to identify the "technology gaps" where current systems cannot meet user expectations and indicate how the latest technologies can be integrated to address these gaps. Functional specifications for ADVISOR will be developed, implemented and evaluated through two test-beds and one demonstrator.
The project will develop real-time computer analysis of multiple video sequences to detect, track and locate individuals in the 3D environment. It will be based on techniques for motion detection, calibration of cameras, scene modelling and object tracking. In addition, crowd-monitoring algorithms developed by CROMATICA will be integrated.
The project will also perform real-time interpretation of the behaviour of individuals and of crowds to recognise anomalous or dangerous situations (such as overcrowding or vandalism) which would require a prompt response from metro staff to maintain smooth running of the transport network. This will be achieved by techniques for event detection and scenario recognition. Moreover, learning techniques will be developed to set thresholds for detecting anomalous situations and prioritising alarms to minimise operator workload.
Within the scope of the project we have tools for the creation, maintenance and searching of a digital video database, using appropriate image coding standards for storing compressed video with automatic annotation according to content, and to assist in the analysis of serious incidents after they have occurred.
The project will develop an ergonomic human computer interface for the display of annotated live video and diagnostics relating to analysis of activities and events that have been detected. The interface will also provide means for the operator to define alarm conditions, verify alarms that are generated and to access the video database. The implementation will use standard commercial hardware configured in an open and scalable architecture.
Milestones:
Functional specifications for ADVISOR are based on analysis of user needs and definitions of the model scenarios which will be used to evaluate performance. These scenarios will be supported by video data supplied by end users from various sites. The first Test Bed (TB) for laboratory evaluation of the individual processing functions based on a single recorded video input. The major functional components of TB 1 are: Camera calibration and scene modelling; local storage of video; monocular tracking of people; crowd flow monitoring; simple event detection and object description; preliminary HCI (Human Computer Interface). The second TB for evaluation of the integrated processing functions will use data recorded at end user sites. It will take multiple inputs from pre-recorded video collected from multiple time-synchronised cameras.
The major functional components of TB 2 are:
Updated version of the HCI;
multi-camera tracking of people;
behaviour description and classification;
multi-camera storage of annotated images with off line search of the resulting archive.
The tracking and behaviour recognition functions will now operate from multiple video inputs with overlapping views to allow targets to be tracked as they move between the views of cameras linked by the ADVISOR system. The demonstrator will be installed at one or more major EU metro sites, will link the ADVISOR system to live camera feed.
Its major functional components are:
Full on site installation and demonstration of the system, including storage of annotated multi camera images with auditable trail and watermarking;
demonstration of system learning by operator interaction;
demonstration of system adaptation to changing light levels.
The crowd-monitoring module of TB 2 will be updated to interact with live camera input and other ADVISOR components. The system components of TB 2 will be installed on a number of separate video workstations with communications through a defined interface across a LAN.
The software tool developed during the project ("PSEconomy") has been successfully demonstrated to meet all of the initial objectives of the programme. It has been shown during the case study and demonstration phase (WP6) to provide the user with a very flexible software system capable of:- detailed thermodynamic performance evaluation- detailed through-life economic performance evaluation based on user-selected operational, economic and market scenarios- complex through-life economic and performance optimisation (user-selectable)All of these features include design-point and off-design component and cycle performance assessment thus enabling complex operational and commercial scenarios to be modelled. The component model library which has been developed for this project, and which now resides within the framework of the IPSEpro/PSEconomy software, provides the user with a large number of "standardised" component models for manipulation within new and novel gas turbine cycles. Each of these component models (where applicable) contains design-point and off-design performance models, an investment cost model and a maintenance cost model.
These component models are by their nature "generic" and therefore represent standardised or typical performance and cost models such that any user has the ability to construct new cycles without the need to build new component models. The case study examples of WP6 have confirmed that the new tool can expedite significant through-life cost reductions and improvements in financial and emissions performance. It has also demonstrated the flexibility of the tool in terms of its ability to optimise cycle or economic parameters depending on the particular requirements of the User.
The relevance of this project to the priorities for call 1999/C77/14 has been significant and is summarised in the following: More energy efficient gas turbines (5.1.3)
- Significant efficiency improvements can be derived through the deployment of the GTPOM tool, through appropriate selection of optimiser objective function. Importantly, the GTPOM tool also provides European industry with the capability to optimise through-life cost, based on the trading of capital cost, fuel cost, operations & maintenance costs and other contributing factors to through-life economic performance.
- Low maintenance aiming at >90% availability and 95% reliability (on an annual basis) for the short and medium term, and 97% reliability for the longer term. The modelling of maintenance cost in the economic evaluations of GTPOM enables application-specific targets to be set for maintenance requirements, based on the needs of the end-user and the overall performance of the plant.
- The target is also to have the capability to use fuels with an LHV<25% of that of natural gas, having emission levels below 20ppmv (NOx) in the medium to long term.
The generic nature of the GTPOM tool, and the extensive component model library contained within the software, enables novel cycles using alternative fuels to be modelled and assessed both for their thermodynamic and economic performance. Optimisation of CHP systems (5.1.4) The results of the GTPOM project will help achieve the all parts of this priority:- The target is to optimise overall efficiency, reducing the specific investment and operating costs by >20% in the short term. The GTPOM tool specifically addresses this priority when performing through-life economic performance optimisation. Net present value improvements significantly in excess of 20% have been seen from the example case studies. - In the longer term, to achieve a mean CO2 reduction of 0.6 kg/kWh produced by CHP as opposed to separate GT power and heat generation. The case studies have demonstrated that advanced cycle configurations, including those specifically intended for CO2 reduction applications, can be modelled and evaluated by the GTPOM tool.- A further short to medium term target is for systems based on conversion of biomass above 40kW, with high reliability and availability, and high electricity to heat ratio and electric efficiency (>20% for small to medium scale, >40 % beyond 35 MWe). Again the case studies have demonstrated that advanced cycle configurations, including those specifically intended for biomass applications, can be modelled and evaluated by the GTPOM tool.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors optical sensors
- engineering and technology electrical engineering, electronic engineering, information engineering electrical engineering power engineering electric power generation combined heat and power
- natural sciences computer and information sciences artificial intelligence computer vision
- engineering and technology environmental engineering energy and fuels
- social sciences social geography transport public transport
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Coordinator
KT15 2NX ADDLESTON, WEYBRIDGE, SURREY
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.