Leveraging SQL for Effective Data Acquisition in Wireless Sensor Networks: An Empirical Approach

Wireless Sensor Networks (WSNs) have gained immense popularity across diverse fields, including industrial monitoring, environmental surveillance, smart cities, and healthcare. These networks have demonstrated their significance in tackling real-world issues by autonomously monitoring, sensing, and wirelessly transmitting data from remote areas. They play a vital role in applications such as monitoring machine and equipment conditions in industries, managing traffic and monitoring air quality in smart cities, and detecting natural disasters like floods, earthquakes, and forest fires in environmental monitoring. However, the wide-scale implementation of WSNs necessitates overcoming critical challenges, such as cost-effective hardware design, energy optimization for improved network performance, secure data communication protocols, and efficient data acquisition, aggregation, and processing techniques. Addressing these challenges is pivotal for the success and sustainability of WSNs, especially as they become increasingly ubiquitous across various domains. This research focuses specifically on data acquisition for WSNs. It investigates multiple aspects of data acquisition and query processing in WSNs and proposes an effective data acquisition approach leveraging robust structured query language (SQL). In contrast to simulation-based evaluation, a real world sensor network testbed is developed and used to validate the proposed approach. Furthermore, the proposed data acquisition approach is evaluated through conducting a usability study. The results of the usability study are encouraging, which indicate that the proposed scheme is an effective and feasible solution for acquiring data from sensor fields in WSNs from the end users perspective.