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Context-A ware Team Task Allocation to Support Mobile Police Surveillance

机译:支持移动警察监视的情境感知团队任务分配

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To optimally distribute tasks within police teams during mobile surveillance, a context-aware task allocation system is designed and evaluated with end-users. This system selects and notifies appropriate team members of current incidents, based on context information (officer availability, officer proximity to the incident and incident priority) and decision rules. Eight teams of three experienced police officers evaluated this system in a surveillance task through a virtual environment, comparing it to a non-adaptive system. Task performance, communication, workload and preferences were measured. Results show that team communication, decision making and response times improve using the adaptive system and that this system is preferred. We conclude that context-aware task allocation helps police teams to coordinate incidents efficiently.
机译:为了在移动监视期间在警察团队内最佳地分配任务,设计了一个上下文感知任务分配系统,并与最终用户进行了评估。该系统根据上下文信息(人员的可用性,人员对事件的接近程度和事件优先级)和决策规则来选择当前事件并通知适当的团队成员。由三名经验丰富的警官组成的八个团队通过虚拟环境在监视任务中评估了该系统,并将其与非自适应系统进行了比较。评估了任务绩效,沟通,工作量和偏好。结果表明,使用自适应系统可以改善团队沟通,决策制定和响应时间,并且该系统是首选。我们得出结论,情境感知任务分配可以帮助警察团队有效地协调事件。

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