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Do not fidget! WiFi will depend you

Credit score: CC0 Public Area

Researchers in UC Santa Barbara professor Yasamin Mostofi’s lab have enabled, for the primary time, counting a stationary seated crowd utilizing WiFi indicators, and with out counting on individuals to hold a tool. The approach, which additionally counts by means of partitions, wants solely a wi-fi transmitter and receiver exterior the world of curiosity the place the group is seated. It has a wide range of functions, together with good vitality administration, controlling the group measurement throughout a pandemic, enterprise planning and safety.

“Our proposed method makes it doable to estimate the variety of seated individuals in an space from exterior,” stated Mostofi, a professor {of electrical} and laptop engineering at UCSB. “This method makes use of solely the obtained energy measurements of 1 WiFi hyperlink, doesn’t depend on individuals to hold a tool and works by means of partitions.”

The proposed methodology and experimental outcomes appeared within the latest nineteenth ACM Worldwide Convention on Cell Programs, Functions, and Companies (MobiSys).

Within the workforce’s experiments, one WiFi transmitter and one WiFi receiver (each off-the-shelf) are in an space the place quite a few individuals are seated. The transmitter sends a wi-fi sign whose obtained energy is measured by the receiver. Through the use of solely such obtained sign energy measurements, the receiver estimates how many individuals are current—an estimate that carefully matches the precise quantity.






Credit score: College of California – Santa Barbara

This innovation builds on earlier work within the Mostofi Lab, which has pioneered sensing with on a regular basis radio frequency indicators equivalent to WiFi since 2009. For example, their 2018 paper confirmed how WiFi can depend a crowd of cellular individuals. Nonetheless, individuals needed to transfer round to be counted.

“Counting a stationary seated crowd is a significantly difficult downside because of the lack of main physique movement,” stated Mostofi. Her lab’s success on this endeavor is because of the new proposed methodology they developed.

“Whereas the individuals within the crowd are stationary, i.e., with no main physique movement besides respiratory, they don’t keep nonetheless for a protracted time frame and continuously have interaction in small in-place pure physique motions known as fidgets,” Mostofi defined. “For example, they could regulate their seating place, cross their legs, verify their telephones, stretch, or cough, amongst others.”

The researchers have proposed that the mixture collective pure fidgeting and in-place motions of a seated crowd carry essential data on the group depend, and have proven, for the primary time, the way to extract the mixture fidgets and depend the overall variety of individuals primarily based on them.

“Think about the Crowd Fidgeting Durations (CFPs), which we outline because the time durations wherein at the least one individual within the WiFi space is fidgeting, in addition to the Crowd Silent Durations (CSPs), which we outline because the time durations wherein not one of the individuals are fidgeting. These durations are simply extractable from the obtained WiFi indicators,”stated Belal Korany, the principle Ph.D. scholar on the venture. “Intuitively talking, the larger the variety of individuals, the upper the prospect that CFPs are longer and the CSPs are shorter. Thus, these durations implicitly carry data on the overall variety of individuals.”

The researchers then developed a brand new mathematical mannequin that statistically describes the collective fidgeting conduct of a stationary crowd, i.e., the CFPs and CSPs, and explicitly relates them to the overall variety of seated individuals.

In growing their mathematical formulation, they first reveal how this downside resembles a a number of decades-old queuing concept downside, a seemingly unrelated downside from a very completely different discipline. “Queuing concept is a department of arithmetic that research ready traces in techniques that contain the arrival of consumers, who require a service from an entity that features quite a few servers,” stated Mostofi. They then present how the CSPs are just like the occasions when no buyer is at a queue that has infinite servers, whereas the CFPs resemble the occasions when at the least one buyer is being served at such a queue. This then permits them to borrow mathematical instruments from queuing concept to develop a very new approach for counting the overall variety of stationary individuals.

“We’ve got examined this know-how extensively in several places, and with completely different numbers of individuals in a number of completely different seating configurations,” stated Korany. The lab has examined their new know-how with 47 experiments in 4 completely different environments (together with through-wall settings), wherein as much as and together with 10 individuals are seated and behaving usually, whereas a pair of WiFi transceivers make WiFi measurements. Their experiments embody varied events, equivalent to attending a lecture/presentation, watching a film or studying in a library.

Their analysis outcomes present a really excessive counting accuracy, with the estimated variety of individuals being zero or one individual off from the true variety of individuals 96.3% of the time in non-through-wall settings, and 90% of the time in through-wall settings. General, their outcomes present the potential of this new know-how for crowd-counting in real-world eventualities, equivalent to for limiting the overall variety of individuals in a crowd throughout a pandemic.


Crowd counting by means of partitions, with WiFi


Extra data:
Outcomes: internet.ece.ucsb.edu/~ymostofi/CountingStationaryCrowd

Offered by
College of California – Santa Barbara


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Do not fidget! WiFi will depend you (2021, September 13)
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