Using footstep-induced vibrations for occupant detection and recognition in buildings

Drira, Slah; Pai, Sai Ganesh Sarvotham; Reuland, Yves; Olsen, Nils F. H.; Smith, Ian F. C.

doi:10.1016/j.aei.2021.101289

Cited by 13 publications

(8 citation statements)

References 76 publications

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“…The Walking Occupancy Detection (WOD) algorithm is a type of occupancy detection algorithm that uses motion sensors to detect the occupancy of people in a smart building. It is commonly used in smart buildings to optimize energy usage and provide a comfortable environment for building occupants [53,54].…”

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

“…The WOD algorithm uses motion sensors to detect the movement of people in the building. The algorithm identifies a person's walking speed and determines whether they are entering or leaving a space based on the direction of their movement [53,54]. By analyzing people's movement patterns in the building, the algorithm can update the occupancy state by the estimated number of persons in each space.…”

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

“…Step 1: Data collection: Motion sensors are installed in different areas of the building to collect data on the movement of people [53,54]. The sensors may be infrared, ultrasonic, or microwave sensors, depending on the building's layout and requirements.…”

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

“…The WOD algorithm's overall process entails gathering data from motion sensors, detecting the presence of people in each space, estimating their walking speed, and using this data to estimate the number of people present in each space and update the occupancy state appropriately [53,54]. By modifying HVAC and lighting systems according to the occupancy condition of each space, the WOD algorithm can be utilized to optimize energy usage in smart buildings.…”

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

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Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors

Chaudhari,

Xiao,

Cheng

et al. 2024

Sensors

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Smart buildings use advanced technologies to automate building functions. One important function is occupancy detection using Internet of Things (IoT) sensors for smart buildings. Occupancy information is useful information to reduce energy consumption by automating building functions such as lighting, heating, ventilation, and air conditioning systems. The information is useful to improve indoor air quality by ensuring that ventilation systems are used only when and where they are needed. Additionally, it is useful to enhance building security by detecting unusual or unexpected occupancy levels and triggering appropriate responses, such as alarms or alerts. Occupancy information is useful for many other applications, such as emergency response, plug load energy management, point-of-interest identification, etc. However, the accuracy of occupancy detection is limited by factors such as real-time occupancy data, sensor placement, privacy concerns, and the presence of pets or objects that can interfere with sensor reading. With the rapid development of IoT sensor technologies and the increasing need for smart building solutions, there is a growing interest in occupancy detection techniques. There is a need to provide a comprehensive survey of these technologies. Although there are some exciting survey papers, they all have limited scopes with different focuses. Therefore, this paper provides a comprehensive overview of the current state-of-the-art occupancy detection methods (including both traditional algorithms and machine learning algorithms) and devices with their advantages and limitations. It surveys and compares fundamental technologies (such as sensors, algorithms, etc.) for smart buildings. Furthermore, the survey provides insights and discussions, which can help researchers, practitioners, and stakeholders develop more effective occupancy detection solutions for smart buildings.

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Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

Section: Walking Occupancy Detection (Wod) Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors

Chaudhari,

Xiao,

Cheng

et al. 2024

Sensors

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“…However, many of them have privacy concerns or require individuals to wear devices, causing inconvenience and discomfort in daily life. 5 To overcome these limitations, recent advancements in structural vibration sensing found that the floor vibrations induced by human footsteps provide both identity and gait health information, [6][7][8][9][10] such as a person's walking speed, balance, and symmetry. This approach has the advantages of being low-cost, non-intrusive, and device-free, which has great potential to be widely adopted for personalized services (e.g., health monitoring) in smart buildings.…”

Section: Introductionmentioning

confidence: 99%

Robust personalized gait health monitoring through footstep-induced structural vibrations

Dong,

Sun,

Wang

et al. 2024

Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2024

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Person identification is important in smart buildings to enable personalized services, such as monitoring individuals' gait health. Existing studies found that the structural vibrations induced by human footsteps provide both identity and gait health information of individuals, such as a person's walking speed, balance, and symmetry, enabling personalized gait health monitoring in smart buildings. However, footstep-induced structural vibrations not only depend on human walking patterns but also on a person's footwear as the footstep force transmits from the foot to the floor. This co-dependency leads to difficulty in identifying the owner of the footsteps when multiple people share the same space and each person has multiple pairs of footwear. In this study, we characterize the effect of footwear on footstep-induced structural vibrations to recognize individuals even when they wear different pairs of shoes (or barefoot). We develop a new metric named Force Transmissibility (FT) that measures the proportion of forces transmitting from the foot to the floor through the footwear. This metric unifies the effect of diverse shoe types, and we utilize this metric to enable robust person identification among various shoe types. We evaluated our approach through real-world walking experiments with eight shoe types shared by four participants. Our method achieves a 22% improvement in identifying the owner of the footsteps when compared to a baseline without footwear considerations.

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An effective recognition of moving target seismic anomaly for security region based on deep bidirectional LSTM combined CNN

Nie

Wang

et al. 2023

Multimed Tools Appl

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Using footstep-induced vibrations for occupant detection and recognition in buildings

Cited by 13 publications

References 76 publications

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors

Robust personalized gait health monitoring through footstep-induced structural vibrations

An effective recognition of moving target seismic anomaly for security region based on deep bidirectional LSTM combined CNN

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