Internet of Things for Intelligent Traffic Monitoring System: A Case Study in Denpasar

Widyantara, I Made Oka; Sastra, Nyoman Putra

doi:10.14445/22312803/ijctt-v30p130

Cited by 10 publications

(5 citation statements)

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“…In the first category, the sensor returns numerical output results e.g. vehicle counted number for each lane [ 10 ], magnetic field intensity value to detect vehicle presence [ 11 ], road density in terms of traffic flow rate [ 12 ], average velocity for each lane [ 13 ], number of vehicles inside the sensing area [ 14 ] and surrounding vehicle detection with Bluetooth [ 15 ]. These outputs are most useful for statistical data analytics that would give insightful strategies in managing traffic flows on the road.…”

Section: Background and Related Workmentioning

confidence: 99%

Development of near real-time wireless image sequence streaming cloud using Apache Kafka for road traffic monitoring application

Htut

Aswakul

2022

PLoS ONE

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In this paper, the authors have designed and implemented the prototype for a near real-time wireless image sequence streaming cloud with two-layered restoration for a road traffic monitoring application of a small-scale network. Since the proposed design is targeted to implement outdoors where the link or node failure could occur, the fault-tolerant capability must be considered. Having only one layer restoration may not provide a good quality of service. Therefore, a two-layer restoration framework is designed in the proposed system by restoring the network layer with the underlying software-defined wireless mesh network capability and at the local broker selection over the Apache Kafka framework. The monitoring application performance has been investigated for the end-to-end average latency and image loss percentage by outdoor testing for 13 hours from 5:40 P.M. 17th November 2020 to 6:40 A.M. 18th November 2020. The end-to-end average latency and image loss percentage have been found to be within the acceptable condition i.e. less than 5 seconds on average with approximated 10% image losses. The proposed system has also been compared with the traditional ad-hoc network, running the OLSR-based network layer, in terms of the rerouting time, restoration time and end-to-end average latency. Based on the emulated wireless network in controllable laboratory environments, the proposed SDWMN-based system outperforms the conventional OLSR-based system with potentially faster rerouting/restoration time due to SDN central controllability and with only marginally increased end-to-end average latency after re-routing/restoration completion. Algorithm complexity analysis has also been given for both the systems. Both the experimental and complexity analysis results thus suggest the practical applicability of the proposed system. Given this promising result, it is therefore recommended as the future research in further developing from the prototype design into the actual deployment for daily traffic monitoring operations.

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Section: Background and Related Workmentioning

confidence: 99%

Development of near real-time wireless image sequence streaming cloud using Apache Kafka for road traffic monitoring application

Htut

Aswakul

2022

PLoS ONE

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“…Dengan berkembangnya infrastruktur internet, terdapat beragam perangkat lain di luar smartphone dan computer yang telah dapat terhubung internet. Adapun IoT juga erat berhubungannya terhadap istilah machine-to-machine atau M2M [4]. Adapun unsur yang membentuk IoT itu sendiri adalah Artificial intelligence (kecerdasan buatan), sensor dan juga konektivitas.…”

Section: Internet Of Things (Iot)unclassified

Rancang Bangun Sistem Penyiraman Taman Hotel Otomatis Berbasis Internet of Things (Iot) Menggunakan Esp8266

Handika¹,

Hartawan²,

Wirastuti³

2022

SPEKTRUM

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COVID-19 is a virus that attacks the respiratory system, has a negative impact on health. The impact of the pandemic is the reduced number of tourists visiting the island of Bali, making sources of income very limited. This directly has a detrimental impact on hotel managers in Bali. With the policy of reducing the number of employees, it is clearly detrimental to all parties and we can see that several hotel facilities have been damaged, one of which is in the garden. In this final project, a garden watering system based on the Internet of Things was designed using ESP8266. This system works according to a programmed watering schedule, rain sensor readings, and soil moisture sensors. The tool will water the garden when the time conditions are met, the rain sensor detects the absence of rain around the park and also when the relay is active, it flows voltage to the solenoid valve to open the water flow to the Sprinkler. Then the watering data will be sent to the Thingspeak cloud which will also be accessible by applications on smartphones. Monitoring information will be displayed on the LCD and also the application on the smartphone. An IoT-based automatic hotel garden watering system prototype using ESP8266 is able to run according to design.

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“…Pertumbuhan populasi berkontribusi dengan peningkatan jumlah alat transportasi yang akan mempengaruhi risiko meningkatnya pula masalah lalu lintas, seperti kemacetan dan kecelakaan. Untuk itu diperlukan mekanisme penanganan masalah transportasi di kota Denpasar untuk meminimalasir terjadi masalah lalu lintas (Widyantara dan Sastra, 2015).…”

Section: Pendahuluanunclassified

Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

Setiawan¹,

Suryawan²

2020

JTIIK

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Pertumbuhan jumlah kendaraan yang semakin meningkat setiap tahunnya mengakibatkan volume kendaraan yang melintasi ruas jalan semakin padat yang kerap mengakibatkan kemacetan lalu lintas. Kemacetan lalu lintas dapat menjadi beban biaya yang signifikan terhadap kegiatan ekonomi masyarakat. Informasi lalu lintas yang dinamis seperti informasi kondisi lalu lintas secara langsung (real time) akan membantu mempengaruhi aktivitas masyarakat pengguna lalu lintas untuk melakukan perencanaan dan penjadwalan aktivitas yang lebih baik. Penelitian ini mengusulkan model pengamatan kondisi lalu lintas berbasis data GPS pada smartphone, untuk informasi kondisi lalu lintas secara langsung. GPS Receiver pada smartphone menghasilkan data lokasi secara instan dan bersifat mobile sehingga dapat digunakan untuk pengambilan data kecepatan kendaraan secara langsung. Kecepatan kendaraan diperoleh berdasarkan jarak perpindahan koordinat kendaraan dalam satuan detik selanjutnya di konversi menjadi satuan kecepatan (km/jam) kemudian data kecepatan kendaraan di proses menjadi informasi kondisi lalu lintas. Secara menyeluruh model pengamatan berfokus pada tiga tahapan, yaitu akuisisi data kecepatan kendaraan berbasis GPS pada smartphone, pengiriman data kecepatan dan visualisasi kondisi lalu lintas berbasis GIS. Pengujian dilakukan pada ruas jalan kota Denpasar telah mampu mendapatkan data kecepatan kendaraan dan mampu menunjukkan kondisi lalu lintas secara langsung dengan empat kategori keadaan lalu lintas yaitu garis berwarna hitam menunjukkan lalu lintas macet dengan kecepatan kendaraan kurang dari 17 km/jam, merah menunjukkan padat dengan kecepatan kendaraan 17 km/jam sampai 27 km/jam, kuning menunjukkan sedang dengan kecepatan kendaraan 26 km/jam sampai 40 km/jam dan hijau menunjukkan lancar dengan kecepatan kendaraan diatas 40 km/jam. AbstractThe growth in the number of vehicles that is increasing every year has resulted in the volume of vehicles crossing the road increasingly congested which often results in traffic congestion. Traffic congestion can be a significant cost burden on economic activities. Dynamic traffic information such as information on real time traffic conditions will help influence the activities of the traffic user community to better plan and schedule activities. This study proposes a traffic condition observation model based on GPS data on smartphones, for information on real time traffic conditions. The GPS Receiver on the smartphone produces location and coordinate data instantly and is mobile so that it can be used for direct vehicle speed data retrieval. Vehicle speed is obtained based on the displacement distance of the vehicle's coordinates in units of seconds and then converted into units of speed (km / h), the vehicle speed data is then processed into information on traffic conditions. Overall, the observation model focuses on three stages, namely GPS-based vehicle speed data acquisition on smartphones, speed data delivery and visualization of GIS-based traffic conditions. Tests carried out on the Denpasar city road segment have been able to obtain vehicle speed data and are able to show traffic conditions directly with four categories of traffic conditions, namely black lines indicating traffic jammed with vehicle speeds of less than 17 km / h, red indicates heavy with speed vehicles 17 to 27 km / h, yellow indicates medium speed with vehicles 26 km/h to 40 km / h and green shows fluent with vehicle speeds above 40 km / h.

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Internet of Things for Intelligent Traffic Monitoring System: A Case Study in Denpasar

Cited by 10 publications

References 0 publications

Development of near real-time wireless image sequence streaming cloud using Apache Kafka for road traffic monitoring application

Development of near real-time wireless image sequence streaming cloud using Apache Kafka for road traffic monitoring application

Rancang Bangun Sistem Penyiraman Taman Hotel Otomatis Berbasis Internet of Things (Iot) Menggunakan Esp8266

Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

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