Automated Attendance System using RFID and IoT
Volume-7 | Issue-3

IoT Enabled Smart Bin for Waste Management with Incentivized Rewards
Volume-6 | Issue-1

Smart and Explainable Credit Card Fraud Detection Using XGBoost and SHAP
Volume-7 | Issue-2

An IoT-based Smart Security Locker System with OTP Verification
Volume-5 | Issue-3

Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3

DDoS Detection using Machine Learning Techniques
Volume-4 | Issue-1

Design of Deep Learning Algorithm for IoT Application by Image based Recognition
Volume-3 | Issue-3

Cloud-based Library Management and Book Tracking through the Internet of Things
Volume-4 | Issue-4

Advanced Traffic Light Controller using FPGA and ARDUINO
Volume-6 | Issue-2

Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3

Suspicious Human Activity Detection System
Volume-2 | Issue-4

ROBOT ASSISTED SENSING, CONTROL AND MANUFACTURE IN AUTOMOBILE INDUSTRY
Volume-1 | Issue-3

EFFICIENT RESOURCE ALLOCATION AND QOS ENHANCEMENTS OF IOT WITH FOG NETWORK
Volume-1 | Issue-2

Live Streaming Architectures for Video Data - A Review
Volume-2 | Issue-4

IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2

Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3

A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3

IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS
Volume-2 | Issue-1

Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3

Hybrid Intrusion Detection System for Internet of Things (IoT)
Volume-2 | Issue-4

Home / Archives / Volume-6 / Issue-2 / Article-3

Volume - 6 | Issue - 2 | june 2024

Crowd Analyzer using Trilateration and Keep Alive Signals Open Access
Kethsia I  , Domesan U  179
Pages: 106-120
Cite this article
I, Kethsia, and Domesan U. "Crowd Analyzer using Trilateration and Keep Alive Signals." Journal of IoT in Social, Mobile, Analytics, and Cloud 6, no. 2 (2024): 106-120
Published
15 May, 2024
Abstract

Tracking mobile phones in a specific area is crucial for assessing population density and understanding crowd dynamics. Traditional methods rely on Wi-Fi and GPS, but offline techniques like cell tower triangulation offer valuable insights even in areas with limited connectivity. By analyzing the number of mobile phones present, estimated through trilateration using signals from the phone's keep-alive signal, one can accurately estimate the crowd size. This information aids in urban planning, transportation management, event organization, and business strategies. Empowered with such data, decision-makers can optimize resource allocation, enhance safety measures, and improve overall societal well-being through informed decision-making.

Keywords

GPS Wi-Fi Trilateration Cell Tower Keep Alive Signals

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here