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.

Highlights

  • The internet of things (IoT) is expected to transform almost countless industries including retail, manufacturing, energy, healthcare, education, and transportation

  • In Rwanda, especially in Kigali, building a sensor network for Internet of Things (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

  • Received Signal Strength Indicator (RSSI) indicates the strength of the signal power received by a receiving sensor node

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Summary

Introduction

The internet of things (IoT) is expected to transform almost countless industries including retail, manufacturing, energy, healthcare, education, and transportation. 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 help in estimating battery life span. We are trying to find the mathematical model which shows the effect of the RSSI on the power consumption of a receiving GPRS based sensor node and from here we will estimate the sensor node lifetime. Our contribution is to develop a data-driven mathematical model that shows the impact of RSSI on the battery life of GPRS/GSM based sensor nodes in a particular location.

Related Works
Material and Methods
Part 1
Part 2
Important Specification about SIM800L
Experiment Setup
Data Acquisition Part
Scenario1
Scenario2
Scenario3
Scenario4
Data Transmission Part
Data Analysis and Discussion
Sensor Node Current States and Transition
Battery Life Calculation
Battery Life Prediction Model for SIM800L Sensor Node
Findings
Conclusions and Future Work
Full Text
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