Advances in technology and data analysis provide rich opportunities for developing intelligent environments assisting their inhabitants, so-called smart environments or smart spaces. Enhanced with technology, sensors, user interfaces, and various applications, such smart spaces are capable of recognizing users and situations they are in, react accordingly, e.g., by providing certain services or changes to the environment itself. Therefore, smart space solutions are gradually coming to different application domains, each with corresponding specific characteristics. In this article, we discuss our experiences and explore the challenges of a long-term real-world Internet of Things (IoT) deployment at a University campus. We demonstrate the technical implementation and data quality issues. We conduct several studies, from data analysis to interaction with space, utilizing the developed infrastructure, and we also share our actions to open the data for education purposes and discuss their outcomes. With this article, we aim to share our experience and provide real-world lessons learned when building an open, multipurpose, publicly used smart space at a University campus.

The recent years have gradually increased the value of wireless connectivity, making it the de facto commodity for both human users and the machines. In this paper, we summarize our experiences of deploying and managing for over two years the extensive indoor sensor network composed of more than three hundred devices connected over LoRaWAN low power wide area network (LPWAN) technology. We start by detailing the background and methodology of our deployment and then present the results of analyzing the network’s operation over a period of two years, focusing specifically on identifying the reasons after the packet losses. Our results reveal that despite the common assumptions, in a real-life network, the packets are lost not only during the on-air transmission but also within the backbone. Among the other interesting findings are the observed nonuniform distribution of the packet transmissions by the nodes in the networks, the seasonal effects on the packet delivery, and the observed effects of the interferences on network performance. The empirical results presented in the paper provide valuable insight into the performance of a real-life extensive LoRaWAN network deployed in an indoor environment and thus may be of interest both to the practitioners and academics.