Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

Abstract

The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effectively. In this article, we address real-time bio-signal sensor monitoring for responders in disaster scenarios. In particular, we propose the integration of a set of health monitoring sensors suitable for detecting stress, anxiety and physical fatigue in an Internet of Cooperative Agents architecture for search and rescue (SAR) missions (SAR-IoCA), which allows remote control and communication between human and robotic agents and the mission control center. With this purpose, we performed proof-of-concept experiments with a bio-signal sensor suite worn by firefighters in two high-fidelity SAR exercises. Moreover, we conducted a survey, distributed to end-users through the Fire Brigade consortium of the Provincial Council of Málaga, in order to analyze the firefighters’ opinion about biological signals monitoring while on duty. As a result of this methodology, we propose a wearable sensor suite design with the aim of providing some easy-to-wear integrated-sensor garments, which are suitable for emergency worker activity. The article offers discussion of user acceptance, performance results and learned lessons.

From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management

“…One of the most important applications of wearable devices in emergency management and response is in search and rescue operations [5,49]. Wearable devices can be used to monitor vital signs and detect the location of individuals who are trapped or lost in disaster situations.…”

“…In hazardous environments, such as wildfires or chemical spills, wearable devices can detect toxic gases, monitor radiation levels, and provide alerts in case of dangerous conditions. The New York City Fire Department is currently testing wearable devices to monitor the exposure of firefighters to toxic chemicals and gases [12,49].…”

Mobility-Aware Resource Allocation in IoRT Network for Post-Disaster Communications with Parameterized Reinforcement Learning

“…Recently, authorities have deployed various types of robots and drones such as unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), unmanned underwater vehicles (UUVs), mobile robots, health care robots, etc. that can be defined as user equipment (UE) for post-disaster management (PDM) because they can be dispatched to locations which cannot be accessed or too risky to be accessed by human rescuers after a disaster has occurred and yet work nonstop [ 3 , 4 , 5 , 6 ]. Furthermore, the Internet of Things (IoT) and robotic technologies have recently been combined in order to expand the functional capabilities of these robots, commonly called the Internet of Robotic Things (IoRT) [ 7 , 8 , 9 , 10 ].…”