# GPRS Sensor Node Battery Life Span Prediction Based on Received Signal Quality: Experimental Study
###### Abstract  
Nowadays with the evolution of Internet of Things (IoT), building a network of sensors for measuring data from remote locations requires a good plan considering a lot of parameters including power consumption. A Lot of communication technologies such as WIFI, Bluetooth, Zigbee, Lora, Sigfox, and GSM/GPRS are being used based on the application and this application will have some requirements such as communication range, power consumption, and detail about data to be transmitted. In some places, especially the hilly area like Rwanda and where GSM connectivity is already covered, GSM/GPRS may be the best choice for IoT applications. Energy consumption is a big challenge in sensor nodes which are specially supplied by batteries as the lifetime of the node and network depends on the state of charge of the battery. In this paper, we are focusing on static sensor nodes communicating using the GPRS protocol. We acquired current consumption for the sensor node in different locations with their corresponding received signal quality and we tried to experimentally find a mathematical data-driven model for estimating the GSM/GPRS sensor node battery lifetime using the received signal strength indicator (RSSI). This research outcome will help to predict GPRS sensor node life, replacement intervals, and dynamic handover which will in turn provide uninterrupted data service. This model can be deployed in various remote WSN and IoT based applications like forests, volcano, etc. Our research has shown convincing results like when there is a reduction of \(-30\) dBm in RSSI, the current consumption of the radio unit of the node will double. WSN; GPRS sensor node; RSSI; GEKKO APM; LabVIEW +
Footnote †: journal: Information Information  
0000.0a big impact on the whole network cost. In Rwanda, especially in Kigali, building a sensor network for IoT applications that can work on technologies like Lora and Sigfox may imply a higher initial cost because of the geographical situation of the country; this will require a lot of base stations or gateways. The GSM cellular network covers 96.4% of the country [2]. This means that any application based on cellular communication will not cost a lot as the network infrastructure is already in place. In this paper, we are trying to work on GSM/GPRS sensor node which can be used to build a WSN or IoT application in Rwanda, without spending a lot of money and we will try to mathematically demonstrate the impact of received signal strength indicator (RSSI) on the power consumption of GPRS Sensor node which will finally help in estimating battery life span. There is a challenge for sensor nodes supplied by batteries, due to power consumption which will even determine the lifetime of the node and the network in general. The battery energy is influenced by the operating temperature and the total current consumption of the node [3; 4]; apart from this, sampling rate, signal strengths, and network topology affect the battery life of sensor node [5; 6], while other researchers found that factors like energy harvesting, energy transfer, energy conservation, and efficient routing techniques can help in prolongation of the lifetime of a sensor node [7; 8]. The big percentage of power consumed by the sensor node is taken by transceiver or radio section: receiving part 26.67% and the transmitting part 33.3 % [8]. In cellular communication, a mobile phone is communicating with the nearest base transceiver station (BTS); the output power from a mobile phone will depend on received signal strength information (RSSI) at that particular location. If the distance between the mobile phone and the nearest BTS is high, the mobile phone will use a lot of power trying to amplify for getting better reception for that weak signal [9]. On the other hand, if the distance is short the phone will output low power as the signal is strong enough which makes the communication easy.