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Updated: Jul 30, 2025
11:21
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
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Building performance simulations can inform IoT privacy leaks in buildings
Alan Wang1, Bradford Campbell2, Arsalan Heydarian3
1Link Lab, Computer Engineering, University of Virginia, Charlottesville, 22903, USA.
Scientific Reports
|May 10, 2023
Summary
Optimizing sensor placement minimizes privacy risks from Internet of Things (IoT) devices. Physics-based simulations show how strategic sensor placement can capture environmental data without overreaching into sensitive occupant information.
Area of Science:
- Computer Science
- Ubiquitous Computing
- Privacy Engineering
Background:
- Internet of Things (IoT) devices are increasingly prevalent, raising privacy concerns.
- Indoor Environmental Quality (IEQ) sensors, intended for energy and health, can infer sensitive occupant data.
- Light sensors, for instance, can detect occupancy, identity, and screen information.
Purpose of the Study:
- To explore sensor placement as a methodology for mitigating privacy risks.
- To quantify the minimal number of sensor positions needed for sensitive inferences using simulations.
- To develop a workflow for respectful capture of inferable occupant activity.
Main Methods:
- Utilizing physics-based simulation models to analyze sensor data.
- Evaluating sensor placement strategies in various building contexts.
- Developing a device-agnostic and building-adaptive workflow.
Main Results:
- A single, strategically placed sensor can capture holistic environmental states in certain contexts.
- Additional sensors can enhance the granularity of inferred occupant activity.
- Simulation models effectively quantify the necessary sensor positions.
Conclusions:
- Sensor placement is a viable strategy to manage privacy risks associated with IEQ sensors.
- Physics-based simulations offer a powerful tool for designing privacy-aware sensing systems.
- Integrating building simulations into sensing schemes is crucial for real-world applications.
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