Figure 3 from Smart Library Seat, Occupant and Occupancy Information System, using Pressure and RFID Sensors | Semantic Scholar (2024)

An IoT-based smart library seat occupancy and reservation (IoT-SLSOR) prototype is developed, using the Radio Frequency Identification (RFID) and Force Sensitive Resistor (FSR) technologies to improve transparency and builds a relationship between library users and their study facilities.

The result shows seat management system can offer convenient, accurate, more personalized, mobility service to each user.

The problems are addressed by creating a prototype system called PartiSee that can effectively monitor attendance and occupancy through the pressure and the light sensors’ readings that results in preventing cheating and reducing attendance taking time, effort, and error rate.

This study introduces a pioneering detection model that seamlessly amalgamates the Faster R-CNN- based object detection framework with a transfer learning-based object classification algorithm, resulting in a substantial enhancement in seat occupancy recognition accuracy and a reduction in computational resources required for neural network training.

The intelligent information retrieval model is proposed and the smart library system based on the book information retrieval is designed and implemented on hardware platforms to show the performance.

This work comprehensively overviews the AI- and IoT-based technologies in three fundamental aspects: smart service, smart sustainability, and smart security and highlights the trend towards future smart libraries.

The first year of the implementation of radio frequency identification in Middlesex University Learning Resources is described, finding that it is possible to implement RFID without too much lead time, although, had longer been available, some aspects would have gone more smoothly.

The overall system design, along with the modifications made to tackle various real-world problems, are presented, which showed that the system achieves a reasonably high level of accuracy at 91.2%.

A state-of-the-art review of force sensing resistors filtered by the need to identify technologies adequate for wearables concludes that the repeatability is the major issue yet unsolved.

A comparative evaluation similar to a laboratory experiment, but in such a way that one could observe the effects of the design decisions in relatively unconstrained, real world use and give a framework for better understanding a ubiquitous computing system.

A framework that optimises the occupancy analysis over long periods by including information on the transition in occupancy, when people enter or leave the monitored area, is proposed.

A closer look at hourly population in different areas and lessons learned are learned.

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