No abstract

The internet of things (IoT) is one of data revolution area and is the following extraordinary mechanical jump after the internet. In terms of IoT, it is expected that electronic gadgets that are used on a regular basis would be connected to the current of the internet. IPv6 over low-power wireless personal area networks (6LoWPAN) is a one of IPv6 header pressure technology, and accordingly, it is vulnerable to attack. The IoT is a combination of devices with restricted resource assets like memory, battery power, and computational capability. To solve this, RPL or routing protocol for low power Lossy network is deploy by utilizing a distance vector scheme. One of denial of service (Dos) attack to RPL network is blackhole attack in which the assailant endeavors to become a parent by drawing in a critical volume of traffic to it and drop all packets. In this paper, we discuss research on numerous attacks and current protection methods, focusing on the blackhole attack. There is also discussion of challenge, open research issues and future perspectives in RPL security. Furthermore, research on blackhole attacks and specific detection technique proposed in the literature is also been presented.

Among the most severe crash scenarios are those caused by driver’s decisions to manoeuvre the vehicle to the adjacent lanes. In most scenarios, drivers’ intentionally change lanes to take over another slower vehicle and preserving the current vehicle speed especially on highway road. The decision may be fatal for drivers of incoming or approaching vehicles which are not aware of the intention and fail to reduce their vehicle speed to avoid lane change collision. Hence, this study proposes a lane change decision aid and warning system which aims to support the driver’s decision prior to performing the lane change on highway road where vehicles are travelling in a single direction. The system implements vehicle-to-vehicle communication (V2V) via long-range (LoRa) communication technology to alert the host vehicle of approaching vehicles and warns the approaching vehicle when a host vehicle intends to change lane. Visual and audible warning will be triggered as precaution mechanism for both host and approaching vehicle drivers. Experiments shows that V2V using LoRa can provide contextual information which are useful to assist drivers in deciding whether to change lane or not on highway use case settings.

<p><span lang="EN-US">Long range communications technology (LoRa) has been widely used in a variety of applications and researched in different domains to exploit its full potential. Its openness makes it ideal for a variety of internet of things (IoT) installations which further allows opportunities for viable solutions in vehicular communications. Hence, a bibliometric analysis was performed to distinguish the application and growth of the technology specifically in vehicular communications. The scoping review processes from Arksey and O’Malley was applied to guide the review process. The selected scholarly works adhered to the PRISMA-Sc framework where 385 articles from two main electronic databases, i.e., Scopus and Science Direct which discussed LoRa in vehicular communications contexts were assessed. This study aims to: i) examine how LoRa’s research has grown from year 2010 to 2021 among the scholars; ii) determine key areas discussed in LoRa’s vehicular communications research. Findings from 70 studies in the final analysis indicated that LoRa has been widely studied based on application, theoretical or protocol and performance. However, it has not been widely explored in vehicular context. Hence, our findings support the global research community in this context.</span></p>

Long-range (LoRa) technology is vastly developing in a significant country that evolves around the Internet of Things (IoT) interest. Such IoT accomplishments include the development of smart cities, long-range monitoring systems, and M2M industries. LoRa technology is making its mark in vehicle-to-vehicle (V2V) communications, but it is yet to be fully explored. This study focused on developing and establishing communication between two LoRa powered devices and evaluating their performances upon deploying a prototype in an actual environment. The prototype is designed with bidirectional communication between two LoRa nodes that could exchange data for user references. Moreover, in the context of having V2V communication, speed and distance are involved in determining the exchange of data. The performance is evaluated in terms of data transmission consistency and reliability. The experimental results revealed that LoRa is applicable for V2V communication within a specific condition; however, there is a need for a more extensive experiment to be carried for a major rolled out of deployment.

Among the most severe crash scenarios are those caused by driver’s decisions to manoeuvre the vehicle to the adjacent lanes. In most scenarios, drivers’ intentionally change lanes to take over another slower vehicle and preserving the current vehicle speed especially on highway road. The decision may be fatal for drivers of incoming or approaching vehicles which are not aware of the intention and fail to reduce their vehicle speed to avoid lane change collision. Hence, this study proposes a lane change decision aid and warning system which aims to support the driver’s decision prior to performing the lane change on highway road where vehicles are travelling in a single direction. The system implements vehicle-to-vehicle communication (V2V) via long-range (LoRa) communication technology to alert the host vehicle of approaching vehicles and warns the approaching vehicle when a host vehicle intends to change lane. Visual and audible warning will be triggered as precaution mechanism for both host and approaching vehicle drivers. Experiments shows that V2V using LoRa can provide contextual information which are useful to assist drivers in deciding whether to change lane or not on highway use case settings.

A physiological-based driver monitoring system (DMS) has attracted research interest and has great potential for providing more accurate and reliable monitoring of the driver’s state during a driving experience. Many driving monitoring systems are driver behavior-based or vehicle-based. When these non-physiological based DMS are coupled with physiological-based data analysis from electroencephalography (EEG), electrooculography (EOG), electrocardiography (ECG), and electromyography (EMG), the physical and emotional state of the driver may also be assessed. Drivers’ wellness can also be monitored, and hence, traffic collisions can be avoided. This paper highlights work that has been published in the past five years related to physiological-based DMS. Specifically, we focused on the physiological indicators applied in DMS design and development. Work utilizing key physiological indicators related to driver identification, driver alertness, driver drowsiness, driver fatigue, and drunk driver is identified and described based on the PRISMA Extension for Scoping Reviews (PRISMA-Sc) Framework. The relationship between selected papers is visualized using keyword co-occurrence. Findings were presented using a narrative review approach based on classifications of DMS. Finally, the challenges of physiological-based DMS are highlighted in the conclusion. Doi: 10.28991/CEJ-2022-08-12-020 Full Text: PDF