Bluetooth Mesh is a new communications protocol for connecting Bluetooth Low Energy devices in a mesh network; it originates as an alternative solution for home and office automation applications. Being a relatively new technology, there is a need to test Bluetooth Mesh in a realistic working environment to asses its strengths and weaknesses. We implemented a basic proof-of-concept Bluetooth Mesh network in our office building for a well-known office automation application: a smart doorbell. The smart doorbell uses Bluetooth Mesh technology to send and receive event messages inside a building and expand its reach with relay nodes. The network nodes were designed in-house according to the requirements of the application. This paper explores the design in hardware and software of a Bluetooth Mesh network in a real environment considering some evaluation metrics, such as package loss across distance and power consumption. It reports some issues regarding energy consumption and relay features. Results show that this technology performed well in our building automation application when considering factors such as radio transmission power and environment settings to achieve optimal functioning.

Bluetooth low energy is an almost ubiquitous technology currently embedded in billions of power-constrained Internet of Things devices around the world. The Bluetooth mesh profile, released by the Bluetooth Special Interest Group in July 2017, allows Bluetooth low energy devices to form a mesh network, further enabling smart home and building applications where long-range connectivity is required. However, the current release of Bluetooth mesh profile still has power and deployment constraints that limit its applicability. To explore the viability of Bluetooth mesh profile in home/building automation applications, we built the Smart Doorbell: a proof-of-concept Bluetooth mesh profile–based visitor notification system for office spaces. The Smart Doorbell was implemented using a mesh network topology with nodes distributed across office building floors, serving as a real Internet of Things deployment and as a testbed for mesh network protocols. Similar Bluetooth mesh profile evaluations found in literature use mostly development kits and/or synthetic traffic in artificial settings; we contribute by using the Smart Doorbell, a system as close as possible to a minimum viable product, to evaluate power consumption and responsiveness as a proxy for product viability. This article presents the architecture of the Smart Doorbell, the viability evaluation results, and a direct comparison with FruityMesh, a competing Bluetooth low energy mesh network protocol. Overall, the fact that Bluetooth mesh profile devices can directly communicate with a user’s mobile phone (using Bluetooth low energy) considerably eases deployment and provisioning. However, the use of flooding to forward messages across the mesh network increases power consumption, precluding the use of battery-powered nodes on the network’s backbone and severely limiting the applicability of Bluetooth mesh profile in building automation.

As algorithmic systems increasingly mediate human activities across diverse domains, they shift more responsibility for data collection onto users, fundamentally altering the nature of data work. This paper examines the implications of this shift by investigating student-led data collection and automated feedback interpretation using a mobile, multimodal learning analytics (MMLA) tool designed to coach oral presentation skills. Our findings reveal that while this user-controlled data collection provides greater flexibility, it also imposes speculative labor, compelling students to adjust their behavior to align with perceived standards of good data even when such changes are unwarranted. The study highlights the often-overlooked informal labor involved in managing the socio-material conditions of data collection, emphasizing the need for MMLA tools that offer adaptive support and guidance. These insights extend to algorithmic system design in educational and professional contexts, advocating for systems that balance user autonomy with workload-minimizing guidance to achieve equitable accountability.