International Research Journal of Engineering and Technology (IRJET) Volume: 11 Issue: 04 | Apr 2024
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
SIMULATION AND ANALYSIS OF WIRELESS DEVICE TRACKER USING PROTEUS Dr. Ajit Kumar Patro1, D Pratyusha2, Jhami Manisha2, G Pravalika Gouri2, Voona Ritika2 1Assistant Professor, ECE department, GIETU, Gunupur, Odisha, India 2UG Scholar, ECE department, GIETU, Gunupur, Odisha, India
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Abstract - The widespread use of mobile phones in
contemporary life has created both benefits and difficulties. Due to worries about security, privacy, and adherence to nophone zones, mobile phone detection has taken on a substantial amount of significance. This paper offers a thorough analysis of mobile phone detection methods and the many uses for them. The main emphasis is on methods, including RF signal analysis, networkbased detection, device fingerprinting, and machine learning-based approaches. The paper also analyses developing technologies, their benefits, drawbacks, and probable prospects for mobile phone detection in the future. Addressing security and privacy problems in a variety of settings, from workplaces and educational institutions to high-security facilities, requires an understanding of and advancement in mobile phone detection technologies. Key Words: RF signal, Communication potential, Resistor, IC LM358, BC548.
1.INTRODUCTION The usage of mobile phones has become pervasive today, making the necessity for efficient mobile phone detection systems critical. Despite their enormous convenience and communication potential [1]. Mobile phones can pose severe security risks or cause disruptions in places where their use is restricted. By detecting the use or existence of mobile phones inside a certain location, mobile phone detectors act as a vital tool in reducing these worries. A device that makes use of wireless signals, for instance WiFi, Bluetooth, or GPS, to monitor and locate other gadgets is referred to as a wireless device tracker. It helps improve asset management, security, and device optimization through the continuous monitoring of mobile phones, tablets, and Internet of Things devices. By offering insights into device mobility and usage trends, these trackers improve efficiency across a range of industries, including logistics, healthcare, and retail. They also provide exact location data. © 2024, IRJET
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Impact Factor value: 8.226
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Mobile devices are identified and located by mobile phone detectors using a variety of technological methods. These methods include machine learningbased techniques, network-based detection, device fingerprinting, and radio frequency (RF) signal analysis [2]. The goal is to reliably identify radio frequency signals from mobile phones and separate them from other signals to ensure adherence to no-phone zones or security. To avoid covering the entire target region, the detection circuit was installed in the research on a constant specified area. Second, the mobile robot unit was operated without the usage of any software due to the Bluetooth module [3]. Given the constraints, this study will address and present ideas to improve the performance of the mobile robot that detects cell phones in making use of a mobile robot's customized cell phone detection circuit and the detector sending a signal to trigger an alarm and then allowing the primary computer user to temporarily disable any unwanted cell phone connections by executing the jammer Yt_003 [4]. Using a camera mounted in front of a mobile robot to wirelessly transmit a video monitoring signal to the main computer. Developing a graphical user interface (GUI) control panel using a customized HTML script that allows the user to navigate and control the mobile robot in the target zones while turning on and off the jammer [5].
2. LITERATURE REVIEW A system that controlled the presence of GSM signals from an illegal user in prohibited zones was devised by Dar et al. in 2014 [6]. Another device could be activated by that system to prevent consumers from using services. Additionally, the device provides GSM frequency signal jamming upon detection to stop any unwanted connections. Nyamawe and Mtonyole introduced another cell phone detection circuit, this time utilizing an Arduino microcontroller [7]. Instead of personally inspecting students upon entry, the Arduino detecting circuit is utilized to replace the current methods of ensuring that they do not have their phones in their pockets during tests. Following these earlier ISO 9001:2008 Certified Journal
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