Abstract

A smart library is designed to bring digital intelligence to objects and spaces, enabling real-time data-informed decisions. This aspect is enabled by the use of sensors that are connected to the internet, all collecting and sharing data and, in this case, data about traffic information in the library, enabling users to book seats, pinpoint locations of vacancy, and intentionally manage energy (power) and resources (labor). The benefit of monitoring occupancy data is introducing an efficient communication channel, revolutionizing a traditional library into a data source hub. This allows a smooth interaction with the user, monetization of the service, adjustment of spatial design and traffic flow, and movement to greener spaces. This paper provides an approach to the above advantages by incorporating a hardware system involving Passive Infrared (PIR) sensors, a node Micro-controller Unit (MCU), and a web app. The prototype system allows seat booking, calculation of library credits, and library occupancy prediction using the Random Forest model and Random Forest Regressor to optimize space allocation and resource management.

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