WIFI TECHNIQUE USES FIDGETING TO COUNT A SEATED CROWD

WIFI TECHNIQUE USES FIDGETING TO COUNT A SEATED CROWD

This method, which also counts through walls, requires only a wireless transmitter and receiver outside the seating area. It has a wide range of applications, including smart energy management, majority size control, business planning and security during pandemics.

Yasmin Mostofi, professor of electrical and computer engineering at the University of California, Santa Barbara, says: “Our proposed approach makes it possible to count the number of people sitting outside.”

The proposed method and test results will appear at the 19th ACM International Conference on the Latest Mobile Systems, Applications and Services (MobiSys).

conduit fittings
During the team’s tests, a WiFi transmitter and a WiFi receiver (both off the shelf) were in the seating area. The transmitter sends a wireless signal, the power of which is measured by the receiver. Using a measure of received power, the recipient makes an estimate of how many there are – an estimate that closely matches the actual number.

The discovery builds on previous work at the Mostofi Laboratory, which since 2009 has been a leader in understanding everyday radio frequency signals such as WiFi. However, people need to count.

“The lack of basic physical movement makes it difficult to count the crowd,” Mostofi said.

“When people in a crowd are immobile, i.e. with no major body movements other than breathing, they do not last long and are often interacted with small natural body movements called fidgets,” Mostoff explained. “For example, they may adjust their sitting position, shorten their legs, check the phone, stretch or cough.”

The researchers suggested that the combined natural movement and motion of the seated majority contained important information about the majority’s number, and showed for the first time how to derive integrated fidgets and calculate the total number. people based on them.

“Consider Crowd Flexibility Periods (CFP), which we define as periods when at least one person is fit into the WiFi area, as well as Crowded Mileage Periods (CSP), which we define at any given time. They do not. These periods are easily derived. From the received WiFi signal.” Elementary PhD student Belal Corny said, “Wisely speaking, the higher the population, the higher the CFP and the lower the CSP are more likely. Therefore, these periods are indirect. generally carries information to the total population.”

The researchers described a new statistical model by describing the collective behavior of a fixed majority, that is, CFP and CSP, and correlating them explicitly with the total number.

technical test
In developing his mathematical formula, he revealed for the first time how this problem resembles a decades-old problem in hierarchical theory. “Queue theory is a branch of mathematics that reads out waiting lines in systems that include the arrival of customers, which requires a service from a company that includes multiple servers,” he said. by Mostopi.

They show how CSPs are analogous to endless servers in non-client queue order, while CFPs are analogous to times when a client serves at least one such queue. It also allows one to borrow mathematical tools from hierarchical theory to come up with an entirely new method for computing fixed population numbers.

“We have tested this technology in detail with different people in different locations and with different seating arrangements,” Kurani said. The lab tested their new technology in four different environments (including wall systems), where 10 people sat and behaved normally, while WiFi transceivers perform a pair of WiFi measurements. Their experiments represent various occasions such as attending lectures/presentations, watching movies or studying in the library.

Their analytical results show the highest numerical accuracy, with an estimated number of zero or real individuals occurring 96.3% of the time in wall invalid systems, and 90% of the time in full wall systems. Overall, their results demonstrate the potential of this new technology to calculate most real-world events, such as controlling the total number of people in a crowd during an outbreak.

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