Multiple Human Tracking Using Binary Infrared Sensors

Area of Science:

• Computer Science
• Robotics
• Human-Computer Interaction

Background:

• Context-aware environments require understanding human location and movement.
• Existing methods may require complex sensor setups or prior knowledge of occupant numbers.

Purpose of the Study:

• To develop an algorithm for tracking human movement paths using only ceiling-mounted infrared (IR) sensors.
• To enable estimation of multiple human movement paths without prior knowledge of the number of individuals.

Main Methods:

• Utilized binary sensed data from infrared (IR) sensors installed on the room ceiling.
• Implemented a prediction and estimation approach, linking previous human positions to newly estimated ones over time.
• Algorithm dynamically traces human movement paths based on sequential position data.

Main Results:

• The proposed algorithm successfully estimated multiple human movement paths.
• The system demonstrated the ability to track paths dynamically without prior knowledge of the number of humans.
• Simulation-based evaluations confirmed the algorithm's effectiveness in tracing movement paths.

Conclusions:

• The developed algorithm provides an effective method for human path tracking using simple IR sensors.
• This approach contributes to creating context-aware environments by accurately mapping human trajectories.
• The method's ability to handle an unknown number of individuals enhances its practical applicability.