Device-based Real-time Single User Indoor Localization Using Internet of Things

Background: Localization is an important area of implementation of the internet of things based on Wireless Sensor Networks. Outdoor user tracking is possible using the global positioning system; however, the global positioning system accuracy decreases in indoor environments. To overcome this problem, the wireless sensor network is used in internet of things-based technology for localization. Objective: The wireless sensor network-based indoor localization is categorized into two categories; range-based and range-free localization. In range-based localization, it first computes the relative distance and then calculates relative coordinates. In range-based techniques, distance and position are calculated. The internet of things-based localization uses the range-based and range-free techniques of a wireless sensor network to localize any object. The Light Dependent Resistor-based localization work has been proposed in previous research. In this research, the light-dependent resistor traces a person’s entry /exit event as the person switches ON/OFF lights of the building. However, it was not a sufficient effort to localize a person using light dependent resistor. To overcome the problem of light dependent resistor, the two PIR sensors have been used in each room along with one RFID based approach in this study. Methods: An indoor scenario has been considered in this study. The hardware setup has been configured to trace the user. When a user enters inside a building, he will switch on the lights, and the light sensor records the light intensity and gives some reading. The difference in the reading of the light sensor (before switching ON the light and after switching OFF the light) gives some clue about a user in an indoor scenario. Nevertheless, if the lights of many rooms remain switched ON, then the user cannot be localized using the above method. In order to sort out this ambiguity of light sensors, two passive infrared sensors in each room along with one radio frequency identification-based model have been proposed in the present study. Implementing the single-user localization using a light-dependent resistor sensor becomes erroneous if a person moves from one room to another and the lights get turned ON/OFF. Moreover, the LDR-based model is affected by sunlight during the daytime. Results: As the implementation of passive infrared sensors along with one RFID-based localization technique gives 93% efficiency, the light-dependent resistor-based localization system gives an efficiency of 35%. Conclusion: The light-dependent resistor-based approach is prone to more errors because the user may enter multiple rooms while the lights of each room remain ON. To overcome this problem, a passive infrared sensor and radio frequency identification-based approach for a single user indoor localization has been proposed. The proposed techniques are easy and cost-effective for implementation. The results show that the proposed technique provides better localization accuracy than a light-dependent sensor-based technique for single-user indoor localization. © 2022 Bentham Science Publishers.