A people-centric sensing approach to detecting sidewalk defects

Abstract

A defective sidewalk inhibits the walkability of a street and may also cause safety accidents (slips, trips, and falls) for pedestrians. When a pedestrian walks along a sidewalk, his/her behaviors may vary according to the condition of the sidewalk-e.g., whether the surface is normal, holed, cracked, tilted, or sloped. As a result, the pedestrian's stability may also change according to the built environment's conditions. Accordingly, this paper examines the feasibility of using pedestrians' physical behaviors to detect defects in a sidewalk. Pedestrians' physical responses and paths over a sidewalk are collected using an inertial measurement unit (IMU) sensor and a global positioning system (GPS). Then, after aggregating the pedestrians' bodily responses and locations, the irregularity of multiple pedestrians' responses are calculated in relation to their locations. The locations that show irregularities in the pedestrian-response patterns present a high correlation with the existence of a defect. The results of this study will help improve the continuous diagnosis of defects in sidewalks, thereby enhancing these built environment systems' serviceability.

Use of Connected Technologies to Assess Barriers and Stressors for Age and Disability-Friendly Communities

“…The physiological responses of older adult pedestrians can be reflective of human experience toward a surrounding environment, providing us unique insights into the elements of the urban built environments (e.g., neighborhood disorders and environmental barriers) ( 19 – 23 ). Various types of physiological response data including gait patterns, electrodermal activity (EDA), heart rate and brain activity ( 22 , 24 – 26 ) have been have been investigated from collected physiological signals in virtual environments ( 27 – 29 ) naturalistic ambulatory settings and daily life locations, such as neighborhoods, downtown, urban parks, and university campuses ( 18 , 20 , 22 , 23 , 30 – 35 ).…”

“…In general, the gait pattern has been shown to correlate with physical barriers of urban built environments such as sidewalk defects, curbs, slopes, and holes ( 19 – 23 , 43 – 52 ) (See Table 1 ). Signals, such as electrodermal activity ( 18 , 21 – 25 , 27 – 31 , 36 – 42 ), electrocardiography or photoplethysmography ( 18 , 20 – 23 , 28 , 36 – 40 , 52 , 53 ) and brain activity ( 26 , 32 , 40 , 54 , 55 ), have been separately used to understand psychological states toward stressors in relation to negative environmental stimuli (e.g., broken houses, barking dogs, and steep stairs) and the mood of walking paths such as urban busy and quiet areas ( 23 , 30 – 32 ).…”

The Feasibility of Information-Entropy-Based Behavioral Analysis for Detecting Environmental Barriers

“…The promotion of physical activity (PA) in the general population is an essential factor that improves public health [ 1 , 2 ]. Numerous previous studies have shown how the built environment influences the behavior of pedestrians [ 3 , 4 , 5 , 6 , 7 , 8 ]. As the most widely practiced form of both transportation and PA, walking and the walking environment have been the focus of many studies [ 9 , 10 , 11 ].…”

“…To identify and address environmental barriers, governmental agencies have undertaken various approaches including inspection by experts and encouraging individuals to self-report [ 8 , 28 ]. In these approaches, inspectors observe the built environment to identify potential environmental barriers and individuals report the environmental features that can act as environmental barriers in their daily living [ 8 , 28 , 29 , 30 , 31 , 32 ]. Although these approaches can identify and create a list of potential environmental barriers, there may be several problems in the process of identifying these impediments.…”

Feasibility Of Wearable-Based Collective Sensing To Detect Environmental Barriers For Facilitating The Elderly’s Mobility

“…To fill this gap, the authors propose the collective sensing (Yang et al, 2017). The collective sensing synthesizes a group of people's signals of interest with location data (e.g., global positioning system (GPS) data) simultaneously to identify locations on which abnormal patterns in the signal occur across the multiple people (Kim et al, 2016;Yang et al, 2017). While a person's stress can be caused by various stimuli, collective stress, which is defined in this study as stress commonly sensed from multiple people on a specific location, can be indicative of a locational stress-inducing factor on the location such as environmental barriers.…”