Using Sedentary Activity Classification Model to Illustrate an Adaptable Freelance Workspace

Obasekore, Hammed; Ajani, Oladayo S.

doi:10.1109/jac-ecc48896.2019.9051183

Cited by 1 publication

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, we propose a novel, specially designed IoT sensor that can be plugged into the user’s monitor and communicates with a server to determine, in real time, user changes in posture, e.g., sitting or standing events, and their presence at their desk. Several prior works have attempted to measure workplace movement [ 4 , 6 , 7 , 8 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. These technologies are at different stages of development.…”

Section: Introductionmentioning

confidence: 99%

A Privacy-Preserving Desk Sensor for Monitoring Healthy Movement Breaks in Smart Office Environments with the Internet of Things

Maiti

Schmidt

et al. 2023

Sensors

View full text Add to dashboard Cite

Smart workplace Internet of Things (IoT) solutions rely on several sensors deployed efficiently in the workplace environment to collect accurate data to meet system goals. A vital issue for these sensor-based IoT solutions is privacy. Ideally, the occupants must be monitored discreetly, and the strategies for maintaining privacy are dependent on the nature of the data required. This paper proposes a new sensor design approach for IoT solutions in the workplace that protects occupants’ privacy. We focus on a novel sensor that autonomously detects and captures human movements in the office to monitor a person’s sedentary behavior. The sensor guides an eHealth solution that uses continuous feedback about desk behaviors to prompt healthy movement breaks for seated workers. The proposed sensor and its privacy-preserving characteristics can enhance the eHealth solution system’s performance. Compared to self-reporting, intrusive, and other data collection techniques, this sensor can collect the information reliably and timely. We also present the data analysis specific to this new sensor that measures two physical distance parameters in real-time and uses their difference to determine human actions. This architecture aims to collect precise data at the sensor design level rather than to protect privacy during the data analysis phase.

show abstract