GPRS-Based Robotic Tracking System with Real Time Video Streaming

Yousif, Tasneem M.; Alharam, Aysha K.; Elmedany, Wael; AlKhalaf, Abeer A.; Fardan, Zainab

doi:10.1109/w-ficloud.2016.67

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…The default setting of the baud rate for the GPRS is 19200. Table 3 displays the AT commands that have been used for the connection of GPRS [9]. The webbased system software with smart applications has been designed and tested, and it is available online, a screenshot of the website system is shown in Fig.…”

Section: Software User Interfacementioning

confidence: 99%

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Development and Hardware Implementation of IoT-Based Patrol Robot for Remote Gas Leak Inspection

Yousif

Elmedany

2022

Int. j. electr. comput. eng. syst. (Online)

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The Internet of Things Robot (IoTR) is an emerging paradigm that brings together robotic systems with the Internet of Things (IoT) that connect sensors and smart objects pervasively embedded in everyday environments. With the recent developments in robotic system applications, it becomes apparent that the mobile robot has great importance in real-world applications such as navigation and surveillance. One of the most important applications of a mobile robot is patrolling and gas leak detection. This paper proposes a real-time IoT Robot (IoTR) that can be used indoors or outdoors for gas leak detection purposes. The proposed mobile robot is equipped with microphones, speakers, the hub of smart sensors that are necessary for patrolling and gas leak detection, a high-resolution IP video camera for live video streaming, Bluetooth for indoor applications and tracking, and GPS/GPRS for outdoor applications and tracking. The experimental testing of the preliminary prototype confirms the design objectives. The robot has been tested for indoor and outdoor modes; the robot can detect gas leakage and provides a live video streaming of the surrounding area, which can be tracked on Google maps. At the same time, the robot can be controlled remotely through a mobile app or website, the robot can move autonomously and avoid obstacles. The proposed work provides a low-cost IoT robot through the use of the available and cheap components and sensors, which featured a high quality at the same time. Our proposed system exhibits promising gas sensing performance in harsh environments, using intelligent gas sensors that have a fast response (>10s), low cost, high sensitivity, long life, robustness, and physical size.

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Section: Software User Interfacementioning

confidence: 99%

“…The presented work in this paper is extended research of the proposed remote monitoring system that has been introduced by [8,9]. The research aims to develop real-time [10] remote monitoring and control IoT robot that is used for security and detecting explosive gases at the same time.…”

Section: Introductionmentioning

confidence: 99%

Development and Hardware Implementation of IoT-Based Patrol Robot for Remote Gas Leak Inspection

Yousif

Elmedany

2022

Int. j. electr. comput. eng. syst. (Online)

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“…the number of successful lane markings the number of white points in ground truth (2) F P R = the number of points markings detected but not exist in ground truth the number of white points in ground truth…”

Section: T Dr =mentioning

confidence: 99%

“…Such a vehicle is equipped with a set of active and passive sensors to perform fonctions, inter alia, obstacles detection and tracking [1,2] objects recognition [3], free space detection [4], global and local vehicle guidance [5]. During the last decade, many researchers have proposed solutions for lateral positioning by embedded cameras.…”

Section: Introductionmentioning

confidence: 99%

Robust Lane Extraction Using Two-Dimension Declivity

Fakhfakh

Chaâri

2018

Artificial Intelligence and Soft Computing

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A new robust lane marking extraction algorithm for monoc ular vision is proposed based on Two-Dimension Declivity. lt is designed for the urban roads with difficult conditions (shadow, high brightness, etc.). ln this paper, we propose a locating system which, from an embedded camera, allows lateral positioning of a vehicle by detecting road markings. The primary contribution of the paper is that it sup plies a robust method made up of six steps: (i) Image Pre-processing, (ii) Enhanced Declivity Operator (DE), (iii) Mathematical Morphology, (iv) Labeling, (v) Hough Transform and (vi) Line Segment Clustering. The experimental results have shown the high performance of our algo rithm in various road scenes. This validation stage has been done with a sequence of simulated images. Results are very promising: more than 90% of marking lines are extracted for Jess than 12% of false alarm.

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