DETECTION OF TRAFFIC DENSITY WITH IMAGE PROCESSING USING PIN HOLE ALGORITHM

The intelligent traffic monitors are devloped and became more interst in recent years. A detection system in the monitoring traffic system is proposed using different algorithms. Pin Hole Algorithm used to detect the car that passes the road (the studied area). A fixed camera mounted at predetermined point used with known height (of the camera), the intensity of the light, and the visibility of the camera. The classification process is important to know the traffic congestion status. The traffic congestion status will be sent to the server address already provided. In the congestion detection test results were obtained with an accuracy value of 85% using the 64x64 grid division and obtaining good detection results for susceptible light intensity values between 5430 and 41379 LUX with an accuracy value of between 60% and 90%. ABSTRAK: Sejak beberapa tahun ini, sistem pengawasan trafik pintar telah dibina dan terus berkembang luas. Sistem pengesanan dalam sistem trafik pengawasan telah dicadangkan menggunakan pelbagai algoritma. Algoritma lubang pin digunakan bagi mengesan kereta yang melalui jalan (kawasan kajian). Kamera dipasang tetap pada titik tertentu iaitu dengan menyelaras ketinggian kamera, keamatan cahaya, dan kebolehlihatan kamera. Proses klasifikasi sangat penting bagi menentukan status kesesakan trafik. Status kesesakan trafik akan dihantar ke alamat pelayan yang telah disediakan. Nilai ketepatan ujian pengesanan kesesakan yang diperoleh adalah 85% iaitu menggunakan pembahagi grid 64x64 dan dapatan kajian menunjukkan pengesanan yang baik bagi nilai keamatan cahaya antara 5430 dan 41379 LUX dengan nilai ketepatan antara 60% dan 90%.

Approach for Collision Minimization and Enhancement of Power Allocation in WSNs

Wireless sensor networks (WSNs) have attracted much more attention in recent years. Hence, nowadays, WSN is considered one of the most popular technologies in the networking field. The reason behind its increasing rate is only for its adaptability as it works through batteries which are energy efficient, and for these characteristics, it has covered a wide market worldwide. Transmission collision is one of the key reasons for the decrease in performance in WSNs which results in excessive delay and packet loss. The collision range should be minimized in order to mitigate the risk of these packet collisions. The WSNs that contribute to minimize the collision area and the statistics show that the collision area which exceeds equivalents transmission power has been significantly reduced by this technique. This proposed paper optimally reduced the power consumption and data loss through proper routing of packets and the method of congestion detection. WSNs typically require high data reliability to preserve identification and responsiveness capacity while also improving data reliability, transmission, and redundancy. Retransmission is determined by the probability of packet arrival as well as the average energy consumption.

RESEARCH ON TRAFFIC CONGESTION DETECTION FROM CAMERA IMAGES IN A LOCATION OF DA LAT

Many researchers are interested in traffic congestion detection and prediction. Traffic congestion occurs increasingly in many cities in Vietnam, including the city of Da Lat. This paper focuses on SVM, CNN, DenseNet, VGG, and ResNet models to detect traffic congestion from camera images collected at Nga 5 Dai Hoc, Da Lat. These images are labeled with the words traffic congestion or no traffic congestion. The experimental results have an accuracy of over 93%. The study is an initial contribution to a future system for predicting traffic congestion in Da Lat when the camera system is fully installed.

RAODV Routing Protocol for Congestion Detection and Relief in Ad Hoc Wireless Networks

Ad hoc wireless networks depend on mutual collaboration among nodes. Congestion in ad hoc wireless networks thus presents more of a challenge than for other network types. This article proposes RAODV (relieving AODV), a modification of the AODV routing protocol, to handle congestion via third party neighbour nodes in dense and static ad hoc networks. RAODV nodes use a T-entropy threshold-based congestion detection algorithm to determine the congestion status of their neighbours. If RAODV determines that congestion is occurring, it then tries to relieve congestion via a local repair modification algorithm that replaces the congested node by a suitable monitoring/third party neighbour node. This article also shows evidence that RAODV results in better network performance than AODV in simulations with random network topologies.