A Unified Deep Transfer Learning Model for Accurate IoT Localization in Diverse Environments

Internet of Things (IoT) is an ever-evolving technological paradigm that is reshaping industries and societies globally. Real-time data collection, analysis, and decision-making facilitated by localization solutions form the foundation for location-based services, enabling them to support critical functions within diverse IoT ecosystems. However, most existing works on localization focus on single environment, resulting in the development of multiple models to support multiple environments. In the context of smart cities, these raise costs and complexity due to the dynamicity of such environments. To address these challenges, this paper presents a unified indoor-outdoor localization solution that leverages transfer learning (TL) schemes to build a single deep learning model. The model accurately predicts the localization of IoT devices in diverse environments. The performance evaluation shows that by adopting an encoder-based TL scheme, we can improve the baseline model by about 17.18% in indoor environments and 9.79% in outdoor environments.

Implementation of a Sustainable Security Architecture using Radio Frequency Identification (RFID) Technology for Access Control

Implementation of a sustainable security architecture has been quite a challenging task with several technology deployed to achieve the feat. Automatic IDentification (Auto-ID) procedures exist to provide information about people, animals, goods and products in transit and found several applications in purchasing and distribution logistics, industries, manufacturing companies and material flow systems. This work focuses on the development and implementation of an access control system using Radio Frequency Identification (RFID) technology to enhance a sustainable security architecture. The system controls access into a restricted area by granting access only to authorized persons, which incorporates the RFID hardware (RFID tags and readers and their antennas) and the software. The antenna are to be configured for a read range of about 1.5 m and TMBE kit reader module was used to test the RFID tags. The encoding and decoding process for the reading and writing to the tag as well as interfacing of the hardware and software was achieved through the use of a FissaiD RFID Reader Writer. The software that controls the whole system was designed using in Java Language. The database required for saving the necessary information, staff/guest was designed using appropriate DataBase Management System (DBMS). The system designed and implemented provide records of all accesses (check-in and check-out) made into the restricted area with time records. Other than this system, Model based modeling through the MATLAB/Simulink, Arduino platform, etc. can be used for similar implementation.