FirstResponse - Revision history

Anita.santanna at 12:39, 25 September 2015

2015-09-25T12:39:28Z

Marcoo at 11:01, 13 January 2015

2015-01-13T11:01:40Z

10.0.2.2: Created page with "{{StudentProjectTemplate |Summary=First response to emergency situation in a smart environment using a mobile robot |Programme=MSc in Embedded and Intelligent Systems, 30 cred..."

2014-03-07T11:53:33Z

Created page with "{{StudentProjectTemplate |Summary=First response to emergency situation in a smart environment using a mobile robot |Programme=MSc in Embedded and Intelligent Systems, 30 cred..."

New page

{{StudentProjectTemplate
|Summary=First response to emergency situation in a smart environment using a mobile robot
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=Image analysis, camera, mobile robot, falls, human-robot interaction, emergency response
|TimeFrame=2014-02-01 / 2014-05-31
|References=Loreto Susperregi, et al. On the Use of a Low-Cost Thermal Sensor to Improve Kinect People Detection in a Mobile Robot. Sensors 2013, 13(11), 14687-14713.

Simin Wang, Salim Zabir, Bastian Leibe. Lying Pose Recognition for Elderly Fall Detection. Proceedings of Robotics: Science and Systems 2011.
|Prerequisites=Image analysis, sensors systems, learning systems, cooperating intelligent systems or similar
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Level=Master
|Status=Ongoing
}}
Smart homes and ambient assisted living applications can support healthy and safe aging at home. One important safety feature is to be able to detect an emergency situation and take appropriate actions in a timely manner. Mobile robots can complement smart homes with additional mobile sensors such as cameras and Kinect sensors. These robots have the ability to more closely investigate a potential emergency situation such as a fall; initiate interaction with the person who has fallen; and decide on what actions to take given the response or lack of response from the person. This project will investigate different sensor modalities and methods to detect falls and potential emergency situations, as well as human-robot interaction modalities; and emergency response actions to ensure the person’s safety.

@@ Line 12: / Line 12: @@
 |Author=Gloria
 |Level=Master
-|Status=Ongoing
+|Status=Finished
 }}
 Smart homes and ambient assisted living applications can support healthy and safe aging at home. One important safety feature is to be able to detect an emergency situation and take appropriate actions in a timely manner. Mobile robots can complement smart homes with additional mobile sensors such as cameras and Kinect sensors. These robots have the ability to more closely investigate a potential emergency situation such as a fall; initiate interaction with the person who has fallen; and decide on what actions to take given the response or lack of response from the person. This project will investigate different sensor modalities and methods to detect falls and potential emergency situations, as well as human-robot interaction modalities; and emergency response actions to ensure the person’s safety.

@@ Line 8: / Line 8: @@
 Simin Wang, Salim Zabir, Bastian Leibe. Lying Pose Recognition for Elderly Fall Detection. Proceedings of Robotics: Science and Systems 2011.
 |Prerequisites=Image analysis, sensors systems, learning systems, cooperating intelligent systems or similar
 |Supervisor=Anita Sant'Anna,
 |Examiner=Antanas Verikas
 |Level=Master
 |Status=Ongoing
 }}
 Smart homes and ambient assisted living applications can support healthy and safe aging at home. One important safety feature is to be able to detect an emergency situation and take appropriate actions in a timely manner. Mobile robots can complement smart homes with additional mobile sensors such as cameras and Kinect sensors. These robots have the ability to more closely investigate a potential emergency situation such as a fall; initiate interaction with the person who has fallen; and decide on what actions to take given the response or lack of response from the person. This project will investigate different sensor modalities and methods to detect falls and potential emergency situations, as well as human-robot interaction modalities; and emergency response actions to ensure the person’s safety.