Summer Research Fellowship Programme of India's Science Academies

Mobile and sensor network based rescue management system

Khushbu Pahwa

Delhi Technological University

Siba Kumar Udgata

University of Hyderabad


In case of disaster, search and rescue operations are performed to locate and rescue victims. However, the effectiveness and efficiency of such rescue operations is often compromised because of the lack of availability of information that could help determine the current location of the person trapped in an emergency situation and thus seeking for help. Moreover, lack of feedback from people under threat or those near them further poses problems to timely rescue of the victim. Wireless sensor networks utilize the technologies which can cause an alert for the immediate rescue operation to begin, whenever this disaster is struck. The proposed mobile and sensor network -based rescue management system (MS-RMS) would cater to this issue in both situations, one in which there is infrastructure support and the other where there is no GSM/CDMA infrastructure support. MS-RMS system thus ensures safety through fast effective response to an emergency situation regardless of the type of the accident or the conscious state of the victim (in the sense that he may be able to place a call or may not be able to do so). Key feature of this system is that it offers mobile and sensor-based solution that helps victims to seek help from the rescue team. The proposed solution can be divided into two stages: (1) The transfer of the vital health care signs of the person to the cloud server (ThingSpeak) along with the GPS location, and setting a threshold for the health care signs, beyond which, a response is required from the rescue team followed by immediate action. (2) In case of infrastructure failure, the data from the sensors attached to the body of the person is transmitted continuously, and the rescue team effectively estimates the location of the person by using the received signal strength indicator (RSSI). Taking into account the environmental factors such as temperature and humidity which affect the RSSI values, we include these as features to train our neural network model that is used to predict the distance.

Keywords: wireless sensor network, ThingSpeak cloud, IoT, MS-RMS, RSSI, ANN


The proposed MS-RMS system caters to providing search and rescue of people in emergency situation in a timely manner which is an extremely important service taking into account the lack of feedback from the victims, which results in lack of timely information needed to determine current location of the person in an emergency situation. These factors make detecting emergencies virtually impossible. This new proposed system aims to improve safety through fast and effective reaction to an emergency situation regardless of type of disaster and capability of user to call for help. We intend to solve this problem by using a wearable sensor composed of NodeMcu, DHT11, Pulse sensor, MPU-6050 (accelerometer,magetometer and gyroscope, and), and GPS which continuously sends the data over to a ThingSpeak server when internet connectivity is available. In case of infrastructure failure, we build an adhoc network of NodeMCUs which send their data to each other by creating a WiFi hotspot. Next, we calculate RSSI values between the Node MCUs as a function of temp and humidity and evaluate their influence on distance using Neural Network. The motivation behind conducting this study is that outdoor localisation has never been explored by researchers in depth as compared to indoor localisation which has led to our interest in developing a system capable of performing search and rescue operations outdoors.

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