阿德雷德大学计算机科学家正在开发一个新的传感器系统，其目的是为了帮助老年人独立、安全地呆在家里。研究人员利用射频识别(RFID)和传感器技术自动识别和监控人的行为，它能判断一个人是否保持正常状态，以便及时为其提供帮助。

    虽然射频识别技术自二战以来就被广泛应用在商场中的反盗窃和公路收费站的车辆识别，其在实验室里的一个潜在应用是用来解释人的行为。阿德雷德大学的首席研究员和资深教授Michael Sheng博士说，“我们的工作是世界上少数通过大尺度的常识性推理对人类行为的自动识别的项目”。

     Sheng博士说，他们提出的这些技术和系统在人口老龄化时代有非常大的潜在价值。他说，对大多数发达国家而言，老年人口比例的迅速增加和劳动力市场的紧缩成为一个非常明显的问题。有许多老年人需要别人来照顾，但是做这件事的人很少。“我们正在通过开发一个无线传感网络与呆在家中的人们进行交互来解决这个问题，利用软件对收集的数据解释之后知道某人正在做什么事情”。

     这些系统成本很低、不显眼、没有隐私问题和可以加强视频临控。它不需要老人配备专门的设备和开关什么装备。

     在过去3年，这项研究得到了澳大利亚研究委员会发现计划的资助，并且他们与昆士兰大学和华盛顿大学展开了相关合作。研究人员将构建一个人类行为识别的射频识别传感器网络；研究一些通过对收集到数据的解释来识别人类行为的算法；通过上下文感知和自动推理感知人们行为模式的变化而且能够及时的交互。

    这些技术在实验室实现之后，然后应用到医院的老年患者。

注：这类技术对于我们日益严重的老龄化问题很有借鉴意义。

附原文：

http://www.adelaide.edu.au/news/news57721.html

Older people: being helped to live at home Full Image (201.92K)

Wednesday, 14 November 2012

University of Adelaide computer scientists are leading a project to develop novel sensor systems to help older people keep living independently and safely in their own homes.

The researchers are adapting radio-frequency identification (RFID) and sensor technologies to automatically identify and monitor human activity; to be able to determine if an individual's normal routine is being maintained so that timely assistance can be provided if it is needed.

Although RFID technology has been around since World War 2 and is in common use today in applications such as anti-shoplifting and vehicle identification at toll road collection points, its potential use in interpreting human activity remains largely in the laboratory.

"Our work will be among the first few projects in the world conducting large-scale common-sense reasoning in automatic human activity recognition," says Chief Investigator and University of Adelaide Senior Lecturer Dr Michael Sheng.

Dr Sheng says the technology and system they propose has huge potential value in an aging population.

"This is becoming a significant problem for most developed countries where the proportion of older people is rapidly increasing and the labour market is tightening - there are more elderly people to be looked after but less people to do it," Dr Sheng says.

"We are trying to solve this by developing a system using a network of sensors attached to objects that the person is interacting with in the home; using software to interpret the collected data to tell us what someone is doing."

The system will be low-cost and unobtrusive and without the privacy issues and intensive monitoring of video surveillance. There will be no need for older people to wear anything or turn anything on or off.

The research is being funded under the Australian Research Council's Discovery Project scheme over three years, in a collaboration with the University of Queensland and the University of Washington.

The researchers will construct an RFID sensor network for human activity recognition; develop an algorithm to allow the interpretation of collected data into recognised activities; and develop context-aware, commonsense-based automatic reasoning so that changes in activity patterns make sense and can produce an alert for timely intervention.

The technology will be first investigated in a laboratory setting and then in hospital trials with geriatric patients.