Vehicular adhoc network (VANET) has a significant potential in reducing traffic congestion to provide a stress-free and safer platform for road drivers to travel on the road. However, the current VANET is vulnerable to several challenges which need to be overcome. Congestion control is considered as one of the main challenges in VANET due to the high dynamic topology characteristic. Reliable congestion control (CC) are necessary to provide effectient dissemination of time-critical safety messages in VANET applications; safety and non-safety applications. In this paper, we present the overview on VANET, its application and challenges. We also discuss on the congestion control and provide a brief survey on the congestion control algorithms such as vehicular cloud computing, multiplicative rate decreasing algorithm, multi-objective Tabu search, D-FPAV algorithm and beaconing strategies which have been proposed in order to provide better solutions towards achieving a successful Smart Tranporation System.

In today’s accelerated growth of mobile device technology, resource utilization in access network will continue to draw more attention to the increasing mobile user devices and applications. The main objective is to address the issue of QoS resource utilization efficiency. This paper combines the Ant Colony Optimization (ACO) algorithm and the Particle Swarm Optimization (PSO) algorithm to provide the optimum routing and to improve the QoS resource utilization efficiency. This proposed hybrid ACO-PSO algorithm uses the IEEE 802.11 DCF standard with multi-antenna scheme (MIMO) of Mobile Ad-hoc Network (MANET) to apply into integrated wireless (MANET) optical (PON network) based in Software Defined Network (SDN) with cloud computing. IEEE 802.11 Wireless Local Area Network (WLAN) gives the opportunity to its users to practice the wireless environment and full functionality of “anything, anytime, anywhere” concept. The proposed work is implemented using the OMNeT++ software where it investigates the QoS performance. These metrics include all nodes throughput, bandwidth, and load balance, routing and control overhead improvement with reduction. They also comprise of RSSI, end to end delay, Packet Delivery Ratio, network capacity, packet loss probability, as well as power consumption in all wireless nodes and energy consumption from wireless domain to wired domain.

The Femto-Macro heterogeneous network is a promising solution to improve the network capacity and coverage in mobile network. However interference may rise due to femtocell deployment nearby to macro user equipment (MUE) within macrocell network coverage. Femtocell offers main priority in resource allocation to its subscribed femto user equipment (FUE) rather than unsubscribed MUE. MUEs will suffer severe interference when they are placed near or within the femtocell area range especially at the cell edge. This phenomenon occurs due to the distance is far from its serving macro base station (MBS) to receive good signal strength. This paper presents a design of cell selection scheme for cell-edge MUE to select an optimal femto base station (FBS) as its primary serving cell in physical resource block allocation. In this study, the proposed cell selection consists of four main elements: measuring the closest FBS distance, Signal to Interference-plus- Noise-Ratio (SINR), physical resource block (PRB) availability and node density level for the selected base station. The main goal is to ensure celledge MUE has priority fairly with FUE in physical resource block allocation per user bandwidth demand to mitigate interference. Hence, the cell-edge MUE has good experienced on receiving an adequate user data rate to improve higher network throughput.

Internet of Things (IoT) is one of the newest matters in both industry and academia of the communication engineering world. On the other hand, wireless mesh networks, a network topology that has been debate for decades that haven’t been put into use in great scale, can make a transformation when it arises to the network in the IoT world nowadays. A Mesh IoT network is a local network architecture in which linked devices cooperate and route data using a specified protocol. Typically, IoT devices exchange sensor data by connecting to an IoT gateway. However, there are certain limitations if it involves to large number of sensors and the data that should be received is difficult to analyze. The aim of the work here is to implement a self-configuring mesh network in IoT sensor devices for better independent data collection quality. The research conducted in this paper is to build a mesh network using NodeMCU ESP 8266 and NodeMCU ESP 32 with two types of sensor, DHT 11 and DHT 22. Hence, the work here has evaluated on the delay performance metric in Line-of-Sight (LoS) and Non-Line-of-Sight (nLos) situation based on different network connectivity. The results give shorter delay time in LoS condition for all connected nodes as well as when any node fail to function in the mesh network compared to nLoS condition. The paper demonstrates that the IoT sensor devices composing the mesh network is a must to leverage the link communication performance for data collection in order to be used in IoT-based application such as fertigation system. It will certainly make a difference in the industry once being deployed on large scale in the IoT world and make the IoT more accessible to a wider audience.

Research and development advancements in the area of Vehicle Door Security using Smart Tag and Fingerprint System. Fingerprint biometric is one of the popular, ubiquitous, reliable, economical and efficient biometric technologies. Due to its versatility, fingerprint biometric is applicable. Fingerprint is popular because of its universality, uniqueness, permanence, acceptability, performance [1]. The Arduino as a controller between RFID Sensor, Fingerprint Sensor, Buzzer, LCD, LED and Relay. This research implemented for security purpose to protect the safety of vehicle from vehicle theft or burglary. It is very useful and important for alert the people who have vehicle to protect it from theft. This is a very important system to be implemented at the main door of vehicle. The system started to work when the user access either than one system fingerprint or smart tag to lock and unlock the door. The fingerprint system only user can access their fingerprint whereas the smart tag system can access by user or user’s intimate relative when they borrow the vehicle for emergency. The vehicle door cannot be opened when unmatched fingerprint is access or incorrect smart tag is access. Once the incorrect smart tag is access by unauthorized person, the buzzer will be activated and produce a high level of alarm sound to alert the user. The Arduino Uno microcontroller is controlled by the entire system of the project. Hence, it is easy to implement and available to use because it has a simple function, so this system can be enhancing with modern technology so it can be applying into vehicle part for secure the vehicle

Indoor positioning has become popular in this decade and is used to locate users or objects in indoor environments. This is because global positioning system (GPS) is not efficient for indoor use due to the multipath fading effect. This research is about development bluetooth low energy (BLE) indoor positioning system with the aid of long range (LoRa) network and guideline on selection of the BLE beacons. Next, positioning systems are developed consisting of BLE beacons, a transceiver of hybrid BLE-LoRa module, a LoRa receiver and Raspberry Pi as real-time monitoring. The received signal strength indicator (RSSI) and BLE Mac address from BLE beacons received via LoRa network are analyzed using the positioning algorithm designed in MATLAB. The positioning algorithm incorporates distance estimation, filter implementation and trilateration technique. The estimated location is analyzed with the root mean square error (RMSE) and cumulative distribution function (CDF). According to the results, implementing the filter reduces the positioning accuracy error, achieving 90% accuracy of positioning error less than 1.20 meters for the whole testbed. Finally, the algorithm is embedded into Raspberry Pi to view the location via desktop.

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This study focuses on mobile ad hoc networks (MANETs) that support Internet routing protocol imposing stringent resource consumption constraints of Quality of service (QoS). The mobile Internet causes the ongoing issue of inefficient use of the MANET resources due to its random nature of wireless environments. In this paper, the new improved architecture of the last mile mobile hybrid optical-wireless access network (adLMMHOWAN) is proposed and designed to tackle the arised issues. The proposed design is based on a unified wireless-wired network solution required the deployment of MANET-based wireless fidelity (WiFi) technology at the wireless front-end and wavelengths division multiplexing passive optical network (WDM PON) at the optical backhaul. The critical performance metrics such as network capacity and energy consumption based on modified AODVUU routing protocol using OMNeT++ software is analyzed with 2 scenarios, namely the number of nodes and mobility speed. This mode of communication results in better QoS network capacity of 47.07% improvement, with 26.85% reduction of lower energy resource consumption for mobile wireless front-end over passive optical network backhaul architecture when compared with the existing work of oRiq scheme that focus on improvement in MANETs.