Proficient car parking system based on cluster head routing protocol utilizing IEEE 802.15.4

The paper discusses a proposed model for car parking system based on cluster head routing protocol utilizing a low cost and power efficient communication technology, ZigBee (IEEE 802.15.4). The model is designed in a way that car parking is divided into different clusters and each cluster has a head which acts a messenger for transmitting information to other heads and the coordinator of the network. Each cluster head is a ZigBee Host (Router) which collects the information of car presence in the parking slot. This information is then passed to the coordinator of the network which is used to display the information of available parking slots in a specific car parking area. Since there is only one coordinator in the network, so heads can transmit information to the coordinator using multi-hop communication if direct communication is not possible. Several simulations were performed to gauge the efficiency of the proposed model, and results show that the proposed model is reliable in communication and efficient in its operation

Multi-radio over fiber architecture for road vehicle communication in VANETs

Vehicular Ad-hoc Networks (VANET) are employing heterogeneous technologies now a days to meet the increasing demands of Intelligent Transportation System (ITS) applications such as enriched multimedia, video conferencing, gaming and online collaboration. Deployment and maintenance cost for infrastructures are also a major concern. This work proposes a framework, capable of catering multiple technologies simultaneously (such as local area network, wide area networks and cellular networks), that deploys wired and wireless integrated technologies to exploit the advantages of both. Therefore, it offers the architecture based on radio over fiber technology to meet the future requirements of high data rate for Road Vehicle Communication (RVC) in VANETs and it comes up with the most important and perhaps desperately needed feature of ‘Future Technology Support’ yielding very high data rates support. Several traditionally deployed architectures are striving to come up with the future needs but due to their various limitations they were unable to attain their expected outcomes. The proposed RoF based architecture justifies its need inducing a true value and powerful features to dramatically enhance the overall performance of the entire system. Several evaluation parameters have been chosen that clearly present the strength of proposed RoF framework and prove that RoF framework is the better option for the service providers in the area of ITS applications

Energy-efficient LoRaWAN for industry 4.0 applications

Thanks to its inherent capabilities (such as fairly long radio coverage with extremely low power consumption), long-range wide area network (LoRaWAN) can support a wide spectrum of low-rate use-cases in Industry 4.0. In this article, both plain and energy harvesting (EH) industrial environments are considered to study the performance of LoRa radios for industrial automation. In the first instance, a model is presented to investigate LoRaWAN in Industry 4.0 in terms of battery life, battery replacement cost, and damage penalty. Then, the EH potential, available within an Industry 4.0, is highlighted to demonstrate the impact of harvested energy on the battery life and sensing interval of LoRa motes deployed across a production facility. The key outcome of these investigations is the cost trade-off analysis between battery replacement and damage penalty along different sensing intervals which demonstrates a linear increase in aggregate cost up to £1500 in case of 5 min sensing interval in the plain (nonenergy harvesting) industrial environment while it tends to decrease after a certain interval up to five times lower in EH scenarios. In addition, the carbon emissions due to the presence of LoRa motes and the annual CO 2 emission savings per node have been recorded up to 3 kg/kWh when fed through renewable energy sources. The analysis presented herein could be of great significance toward a green industry with cost and energy efficiency optimization

Energy harvesting in LoRaWAN: a cost analysis for the industry 4.0

Exploiting the advantages brought by long-range radio communications and extremely low power consumptions, LoRaWAN is capable to support low rate industry 4.0 services. Despite being energy efficient, LoRa motes can still undergo frequent battery replenishments caused by the monitoring requirements of industrial applications. Duty-cycle constrained operations can partially face this issue at the expense of increased communication delays, which, in turn, inflate higher costs due to damaged products on the production line. This letter proposes a model to analyze this cost tradeoff against different sensing intervals. It further highlights the impact of energy harvesting sources on this cost relationship mapping a way toward improved production efficiency

Deployment of VoIP communications in B&A spy agency: design and implementation

VoIP, Voice over Internet Protocol is one of the emerging and bleeding edge technologies that have in most cases sorted out the budget problems for the transmission and reception of voice communications. Indeed it is to use the Data Network infrastructure (Packet Switching Network) for the transmission and reception of voice calls. Though, people do prefer to use circuit switching network as it gives a dedicated path between end users that results in a crystal clear voice quality. Also the Digital communications “Modulation for the Transmitter end” and “Demodulation for the Receiving end” is involved (Digital Signal Processing to provide phenomenal voice quality) but no one can regret a fact that is; occasionally it becomes too expensive for the organization to provide dedicated paths to all employees. A promising solution is yes of course VoIP but the deployment of this technology introduces issues like Voice Quality, Jitter/ Delay, Quality of Service, Denial of Service etc. which is a challenge. In order to deploy VoIP communications in an existing Network it is very crucial and important to do proper planning and to analyze the network critically and justify whether it the Network is ready to cope with the VoIP services, as it can cause serious effects to the Network in case it is over burden. After doing that to assess and then evaluate by testing the network. This research is a case study based on B&A, A spy agency that has faced problems in the future regarding to call management and expansion. This research will cover the design and implementation of VoIP simulated in OPNET

Evaluation of low power mobile devices in intelligent transportation systems

The paper discusses the use of mobile devices like smart phones and tablets in Demand Responsive Transit (DRT). The paper will specifically focus on a special DRT called “Flexible Bus Systems” (FBS). In FBS the routes of the buses are so flexible that even they can take a short route to pick up the passenger waiting at the bus stops by skipping the bus stops where no passenger is waiting to ride the bus and no passenger wants to drop off. The major objective of using the mobile devices in FBS is to provide passengers with real time information of buses, facility of booking bus tickets on the fly using their mobile devices. Furthermore, NFC tags are used to help tourists get the information about the city along with bus schedules on their NFC enabled smart devices

Spatio-temporal crime HotSpot detection and prediction: a systematic literature review

The primary objective of this study is to accumulate, summarize, and evaluate the state-of-the-art for spatio-temporal crime hotspot detection and prediction techniques by conducting a systematic literature review (SLR). The authors were unable to find a comprehensive study on crime hotspot detection and prediction while conducting this SLR. Therefore, to the best of author's knowledge, this study is the premier attempt to critically analyze the existing literature along with presenting potential challenges faced by current crime hotspot detection and prediction systems. The SLR is conducted by thoroughly consulting top five scientific databases (such as IEEE, Science Direct, Springer, Scopus, and ACM), and synthesized 49 different studies on crime hotspot detection and prediction after critical review. This study unfolds the following major aspects: 1) the impact of data mining and machine learning approaches, especially clustering techniques in crime hotspot detection; 2) the utility of time series analysis techniques and deep learning techniques in crime trend prediction; 3) the inclusion of spatial and temporal information in crime datasets making the crime prediction systems more accurate and reliable; 4) the potential challenges faced by the state-of-the-art techniques and the future research directions. Moreover, the SLR aims to provide a core foundation for the research on spatio-temporal crime prediction applications while highlighting several challenges related to the accuracy of crime hotspot detection and prediction applications

Features of mobile apps for people with autism in a post covid-19 scenario: current status and recommendations for apps using AI

The new ‘normal’ defined during the COVID-19 pandemic has forced us to re-assess how people with special needs thrive in these unprecedented conditions, such as those with Autism Spectrum Disorder (ASD). These changing/challenging conditions have instigated us to revisit the usage of telehealth services to improve the quality of life for people with ASD. This study aims to identify mobile applications that suit the needs of such individuals. This work focuses on identifying features of a number of highly-rated mobile applications (apps) that are designed to assist people with ASD, specifically those features that use Artificial Intelligence (AI) technologies. In this study, 250 mobile apps have been retrieved using keywords such as autism, autism AI, and autistic. Among 250 apps, 46 were identified after filtering out irrelevant apps based on defined elimination criteria such as ASD common users, medical staff, and non-medically trained people interacting with people with ASD. In order to review common functionalities and features, 25 apps were downloaded and analysed based on eye tracking, facial expression analysis, use of 3D cartoons, haptic feedback, engaging interface, text-to-speech, use of Applied Behaviour Analysis therapy, Augmentative and Alternative Communication techniques, among others were also deconstructed. As a result, software developers and healthcare professionals can consider the identified features in designing future support tools for autistic people. This study hypothesises that by studying these current features, further recommendations of how existing applications for ASD people could be enhanced using AI for (1) progress tracking, (2) personalised content delivery, (3) automated reasoning, (4) image recognition, and (5) Natural Language Processing (NLP). This paper follows the PRISMA methodology, which involves a set of recommendations for reporting systematic reviews and meta-analyses