scholarly journals Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 347 ◽  
Author(s):  
Jonathon Handscombe ◽  
Hong Qing Yu
Keyword(s):  
Traffic Flow ◽  
Mac Protocol ◽  
Low Cost ◽  
Smart Phone ◽  
Base Stations ◽  
Media Access Control ◽  
Flow Data ◽  
Media Access ◽  
Location Data ◽  
Intelligent Traffic System

There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism.

An Adaptive TDMA Slot Assignment Algorithm for Scalable Wireless Mesh Networks

2013 ◽  
Vol 392 ◽  
pp. 872-875 ◽  
Author(s):  
Gu Jia ◽  
Yu Wen Wang ◽  
Fan Ji Meng ◽  
Guo Hua Ye ◽  
Guo Lin Wang
Keyword(s):  
Wireless Mesh Network ◽  
Mesh Networks ◽  
Mac Protocol ◽  
Cluster Head ◽  
Mesh Network ◽  
Frame Structure ◽  
Media Access Control ◽  
Media Access ◽  
Slot Allocation ◽  
Wireless Mesh

The media access control (MAC) protocol based on fixed slot allocation has low throughput and high delay in high load wireless mesh network. In order to improve the performance of wireless mesh network, we propose a scalable adaptive time division multiple access (TDMA) slot allocation algorithm based on the existing fixed TDMA. The algorithm uses the network structure of clustering and builds a more optimized frame structure, cluster head dynamically allocates time slot according to the packet number of the cluster member sent and the priority level, at the same time taking into account the situation of nodes joining and leaving to improve the scalability of the network The simulation results on OPNET network simulation platform show that the algorithm is superior to fixed TDMA algorithm in both throughput and delay.

scholarly journals TIME TRAVEL ESTIMATIONS USING MAC ADDRESSES OF BUS PASSENGERS: A POINT TO PATH-QGIS ANALYSIS

2018 ◽  
Vol 5 (2) ◽  
pp. 263 ◽  
Author(s):  
Arief Hidayat ◽  
Shintaro Terabe ◽  
Hideki Yaginuma
Keyword(s):  
Travel Time ◽  
Mobile Phones ◽  
Open Source Software ◽  
Smart Cities ◽  
Low Cost ◽  
Time Travel ◽  
Media Access Control ◽  
Media Access ◽  
Address Data ◽  
Data Points

Currently, the development of WiFi is proliferating, especially in the field of transportation and smart cities. At the same time, WiFi is a low-cost technology, which offers a longer survey time and is able to support the Big Data era. This paper describes our study, which first uses a WiFi scanner to capture media access control (MAC) address data of bus passengers’ WiFi devices and then identifies each MAC address travel time to confirm the bus passengers. The MAC address is a unique ID for each device used such as mobile phones, smartphones, laptops, tablets, and other WiFi-enabled equipment. The WiFi scanner was placed inside the bus to capture all the MAC addresses inside and around the bus. The survey was conducted for one day (eight hours). The paper describes the procedure of the time travel estimation for each MAC address using the “point to path” analysis in QGIS open source software. This procedure, using point to path-GIS, produced 70,000-80,000 raw data points cleaned into 100-130 new data points. The procedure determined how many passengers traveled and explained which bus passengers used based on travel time.

scholarly journals Time Slot Utilization for Efficient Multi-Channel MAC Protocol in VANETs

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3028 ◽  
Author(s):  
VanDung Nguyen ◽  
Tran Anh Khoa ◽  
Thant Zin Oo ◽  
Nguyen H. Tran ◽  
Choong Seon Hong ◽  
...  
Keyword(s):  
Multiple Access ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Mac Protocol ◽  
Media Access Control ◽  
Delivery Ratio ◽  
Media Access ◽  
Traffic Conditions ◽  
Hoc Networks ◽  
Transmission Overhead

In vehicular ad hoc networks (VANETs), many schemes for a multi-channel media access control (MAC) protocol have been proposed to adapt to dynamically changing vehicle traffic conditions and deliver both safety and non-safety packets. One such scheme is to employ both time-division multiple access (TDMA) and carrier-sense multiple access (CSMA) schemes (called a hybrid TDMA/CSMA scheme) in the control channel (CCH) interval. The scheme can adjust the length of the TDMA period depending on traffic conditions. In this paper, we propose a modified packet transmitted in the TDMA period to reduce transmission overhead under a hybrid TDMA/CSMA multi-channel MAC protocol. Simulation results show that a MAC protocol with a modified packet supports an efficient packet delivery ratio of control packets in the CCH. In addition, we analyze the hybrid TDMA/CSMA multi-channel MAC protocol with the modified packet under saturated throughput conditions on the service channels (SCHs). The analysis results show that the number of neighbors has little effect on the establishment of the number of time slots in TDMA periods and on SCHs under saturated throughput conditions.

scholarly journals TIME TRAVEL ESTIMATIONS USING MAC ADDRESSES OF BUS PASSENGERS: A POINT TO PATH-QGIS ANALYSIS

2018 ◽  
Vol 5 (2) ◽  
pp. 259
Author(s):  
Arief Hidayat ◽  
Shintaro Terabe ◽  
Hideki Yaginuma
Keyword(s):  
Travel Time ◽  
Mobile Phones ◽  
Open Source Software ◽  
Smart Cities ◽  
Low Cost ◽  
Time Travel ◽  
Media Access Control ◽  
Media Access ◽  
Address Data ◽  
Data Points

Currently, the development of WiFi is proliferating, especially in the field of transportation and smart cities. At the same time, WiFi is a low-cost technology, which offers a longer survey time and is able to support the Big Data era. This paper describes our study, which first uses a WiFi scanner to capture media access control (MAC) address data of bus passengers’ WiFi devices and then identifies each MAC address travel time to confirm the bus passengers. The MAC address is a unique ID for each device used such as mobile phones, smartphones, laptops, tablets, and other WiFi-enabled equipment. The WiFi scanner was placed inside the bus to capture all the MAC addresses inside and around the bus. The survey was conducted for one day (eight hours). The paper describes the procedure of the time travel estimation for each MAC address using the “point to path” analysis in QGIS open source software. This procedure, using point to path-GIS, produced 70,000-80,000 raw data points cleaned into 100-130 new data points. The procedure determined how many passengers traveled and explained which bus passengers used based on travel time.

scholarly journals Media Access Control Protocol in Ad Hoc Network Based on Hybrid Antennas

2013 ◽  
Vol 765-767 ◽  
pp. 1956-1959
Author(s):  
Ming Ce Cheng ◽  
Ying Li
Keyword(s):  
Access Control ◽  
Data Transmission ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mac Protocol ◽  
Directional Antennas ◽  
Media Access Control ◽  
Media Access ◽  
Simulation Results ◽  
Media Access Control Protocol

In order to solve the problem of the communication asymmetry problems in hybrid ad hoc network because of the introduction of directional antennas, we propose a hybrid MAC protocol termed DFMAC protocol, which achieving data transmission by one hop through the use of exchange RTS by multiple hops. The protocol takes the benefit of directional antennas and can be used by node equipped with Omni-directional antennas, simulation results show that the DFMAC protocol performs well in improving the network throughput.

scholarly journals Impact of Big Data Analysis on Nanosensors for Applied Sciences Using Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
S. Shitharth ◽  
Pratiksha Meshram ◽  
Pravin R. Kshirsagar ◽  
Hariprasath Manoharan ◽  
Vineet Tirth ◽  
...  
Keyword(s):  
Applied Sciences ◽  
Big Data ◽  
Data Analysis ◽  
Mac Protocol ◽  
Big Data Analysis ◽  
Media Access Control ◽  
Media Access ◽  
Measurement Sensitivity ◽  
Healthcare Applications ◽  
Application Systems

In the current-generation wireless systems, there is a huge requirement on integrating big data which can able to predict the market trends of all application systems. Therefore, the proposed method emphasizes on the integration of nanosensors with big data analysis which will be used in healthcare applications. Also, safety precautions are considered when this nanosensor is integrated where depth and reflection of signals are also observed using different time samples. In addition, to analyze the effect of nanosensors, six fundamental scenarios that provide good impact on real-time applications are also deliberated. Moreover, for proving the adeptness of the proposed method, the results are equipped in both online and offline analyses for investigating error measurement, sensitivity, and permeability parameters. Since nanosensors are introduced, the efficiency of the projected technique is increased by implementing media access control (MAC) protocol with recurrent neural network (RNN). Further, after observing the simulation results, it is proved that the proposed method is more effective for an average percentile of 67% when compared to the existing methods.

scholarly journals A universal Wi-Fi fingerprint localization method based on machine learning and sample differences

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xiaoxiang Cao ◽  
Yuan Zhuang ◽  
Xiansheng Yang ◽  
Xiao Sun ◽  
Xuan Wang
Keyword(s):  
Machine Learning ◽  
Binary Classification ◽  
Low Cost ◽  
Classification Model ◽  
Gradient Boosting ◽  
Media Access Control ◽  
Media Access ◽  
Localization Algorithms ◽  
Extreme Gradient Boosting ◽  
The Media

AbstractWi-Fi technology has become an important candidate for localization due to its low cost and no need of additional installation. The Wi-Fi fingerprint-based positioning is widely used because of its ready hardware and acceptable accuracy, especially with the current fingerprint localization algorithms based on Machine Learning (ML) and Deep Learning (DL). However, there exists two challenges. Firstly, the traditional ML methods train a specific classification model for each scene; therefore, it is hard to deploy and manage it on the cloud. Secondly, it is difficult to train an effective multi-classification model by using a small number of fingerprint samples. To solve these two problems, a novel binary classification model based on the samples’ differences is proposed in this paper. We divide the raw fingerprint pairs into positive and negative samples based on each pair’s distance. New relative features (e.g., sort features) are introduced to replace the traditional pair features which use the Media Access Control (MAC) address and Received Signal Strength (RSS). Finally, the boosting algorithm is used to train the classification model. The UJIndoorLoc dataset including the data from three different buildings is used to evaluate our proposed method. The preliminary results show that the floor success detection rate of the proposed method can reach 99.54% (eXtreme Gradient Boosting, XGBoost) and 99.22% (Gradient Boosting Decision Tree, GBDT), and the positioning error can reach 3.460 m (XGBoost) and 4.022 m (GBDT). Another important advantage of the proposed algorithm is that the model trained by one building’s data can be well applied to another building, which shows strong generalizable ability.

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