Where To Go? Smart Guidance Based On IoT Sensor-Data

Robin Effing*, Robert J. Brouwer, Asen Iliev, Fons Wijnhoven

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


There is an increasing interest in indoor occupation and guidance information for business and societal purposes. Scientific literature has paid attention to various ways of detecting occupation using different sensors as data source including various algorithms for estimating occupation rates from this data. Gaining meaningful insights from the data still faces challenges because the potential benefits are not well understood. This study presents a proof-of-concept of an indoor occupation information system, following the design science methodology. We review various types of sensor data that are typically available or easy-to-install in buildings such as offices, classrooms and meeting rooms. This study contributes to current research by incorporating business requirements taken from expert interviews and tackling one of the main barriers for business by designing an affordable system on a common existing infrastructure. We believe that occupation information systems call for further research, in particular also in the context of social distancing because of covid19.
Original languageEnglish
Title of host publicationConnected Smart Cities CSC2020 as part of the Multi Conference on Computer Science and Information Systems MCCSIS2020
EditorsP. Kommers
Publication statusPublished - 2020
Event14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020 - Online conference
Duration: 21 Jul 202025 Jul 2020
Conference number: 14


Conference14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020
Abbreviated titleMCCSIS 2020
Internet address

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