In recent times, the volume of traffic congestion has been rapidly growing on roads. These days the necessity of having safe transportation and journey is essential. Thus, vehicle communication could be a possible solution to enhance safe transit. Vehicular communications provide a wide range of applications with different characteristics, namely vehicle and vehicle (V2V) communications. Every year, traffic accidents kill many people worldwide, and many people have been injured. V2V communication enables vehicles to communicate with each other to provide safety and convenience to drivers. Therefore, this paper explores a direction to develop a conceptual approach to V2V communication with HC-12, nRF24L01, and XBee. The study aims to analyze and evaluate the communication range that may contribute to the future road transportation system.
Smart optimization in 802.11p media access control protocol for vehicular ad ...IJECEIAES
The innovative idea presented in this research is that advancements in automotive networks and embedded devices can be used to assess the impact of congestion control on throughput and packet delivery ratio (PDR), or socalled multimedia content delivery. Vehicle networking and the distribution of multimedia content have become essential factors in getting packets to their intended recipients due to the availability of bandwidth. Vehicle-toinfrastructure (V2I) communication systems are crucial in vehicular ad hoc networks (VANETs), which permit vehicles to connect by distributing and delivering traffic data and transmission packet schemes. High levels of mobility and changing network topology necessitate dispersed monitoring and execution for congestion control. The amount of traffic congestion for packet transfers could be reduced by enhancing congestion management in terms of throughput and PDR percentages. In a highway setting, the Taguchi approach has been used to optimize the parameters for congestion control. Based on throughput and PDR performance measures, this technique minimizes superfluous traffic information and lowers the likelihood of network congestion. The simulation results have shown that the proposed approach performs better since it increases network performance while effectively utilizing bandwidth. The effectiveness of the suggested technique is evaluated using a typical VANETs scenario for V2I communication while driving on a highway.
Design Approach for Vehicle To Vehicle (V2V) Dissemination of Messages in Veh...IJERA Editor
Designing a protocol structure which contains the control system, VANET device and the type of communication message structures which will implement the message packets for v2v or v2I infrastructure . The different message packets contain the information required to transfer from one node to another in vehicular network for communication. Design various algorithm required for Control, Alert and Infotainment messages. Time stamping lowering data rate efficient packet delivery and proper communication of required messages. Implementation of proposed algorithms and comparison of them with existing algorithms and study of different factors affecting the working of theses algorithms. Analysis of proposed design approach and improvements in results if required.
Effective Road Model for Congestion Control in VANETSijwmn
Congestion on the roads is a key problem to deal with, which wastes valuable time.. Due to high mobility
rate and relative speed link failure occur very often. VANET is used to tackle the problem of congestion,
and make decisions well in advance to avoid traffic congestion. In this paper we proposed a solution to
detect and control the traffic congestion by using of both (V2V) and (V2I), as a result the drivers become
aware of the location of congestion as well as way to avoid getting stuck in congestion. The congestion is
detected by analyzing the data obtained by vehicular communication and road side units to avoid the
traffic. Our proposition system is competent of detecting and controlling traffic congestion in real-time.
V2V and V2I communication network is used to receive and send the messages. We simulate the result by
using Congestion Detection and Control Algorithm (CDCA), and show that this is one effective way to
control congestion. The Proposed methodology ensures reliable and timely delivery of messages to know
about congestion and avoid it.
ANET: Technical and Future Challenges with a Real Time Vehicular Traffic Simu...IJERA Editor
VANET or Vehicular Ad-Hoc Network is a special type of MANET or Mobile Ad-Hoc Network that is
designed specifically for communications between vehicles or V2V and vehicles to infrastructure or V2I. There
is a lot of studies and research that has been dedicated to study this technology due to its importance and
necessity in our life. The fact that each and every module presented must be tested thoroughly before putting it
into action, as there will be severe consequences in case of a system malfunction especially if it's a vehicular
design problem. However, seeing VANETS coming into reality becomes very close with the advancement of
IEEE 802.11p standard that is being dedicated to the DSRC or dedicated short range communication [1]. This
paper will discuss this technology emphasizing some of its applications, current limitations and future challenges
plus simulating a real traffic using SUMO and OpenStreetMap
Smart optimization in 802.11p media access control protocol for vehicular ad ...IJECEIAES
The innovative idea presented in this research is that advancements in automotive networks and embedded devices can be used to assess the impact of congestion control on throughput and packet delivery ratio (PDR), or socalled multimedia content delivery. Vehicle networking and the distribution of multimedia content have become essential factors in getting packets to their intended recipients due to the availability of bandwidth. Vehicle-toinfrastructure (V2I) communication systems are crucial in vehicular ad hoc networks (VANETs), which permit vehicles to connect by distributing and delivering traffic data and transmission packet schemes. High levels of mobility and changing network topology necessitate dispersed monitoring and execution for congestion control. The amount of traffic congestion for packet transfers could be reduced by enhancing congestion management in terms of throughput and PDR percentages. In a highway setting, the Taguchi approach has been used to optimize the parameters for congestion control. Based on throughput and PDR performance measures, this technique minimizes superfluous traffic information and lowers the likelihood of network congestion. The simulation results have shown that the proposed approach performs better since it increases network performance while effectively utilizing bandwidth. The effectiveness of the suggested technique is evaluated using a typical VANETs scenario for V2I communication while driving on a highway.
Design Approach for Vehicle To Vehicle (V2V) Dissemination of Messages in Veh...IJERA Editor
Designing a protocol structure which contains the control system, VANET device and the type of communication message structures which will implement the message packets for v2v or v2I infrastructure . The different message packets contain the information required to transfer from one node to another in vehicular network for communication. Design various algorithm required for Control, Alert and Infotainment messages. Time stamping lowering data rate efficient packet delivery and proper communication of required messages. Implementation of proposed algorithms and comparison of them with existing algorithms and study of different factors affecting the working of theses algorithms. Analysis of proposed design approach and improvements in results if required.
Effective Road Model for Congestion Control in VANETSijwmn
Congestion on the roads is a key problem to deal with, which wastes valuable time.. Due to high mobility
rate and relative speed link failure occur very often. VANET is used to tackle the problem of congestion,
and make decisions well in advance to avoid traffic congestion. In this paper we proposed a solution to
detect and control the traffic congestion by using of both (V2V) and (V2I), as a result the drivers become
aware of the location of congestion as well as way to avoid getting stuck in congestion. The congestion is
detected by analyzing the data obtained by vehicular communication and road side units to avoid the
traffic. Our proposition system is competent of detecting and controlling traffic congestion in real-time.
V2V and V2I communication network is used to receive and send the messages. We simulate the result by
using Congestion Detection and Control Algorithm (CDCA), and show that this is one effective way to
control congestion. The Proposed methodology ensures reliable and timely delivery of messages to know
about congestion and avoid it.
ANET: Technical and Future Challenges with a Real Time Vehicular Traffic Simu...IJERA Editor
VANET or Vehicular Ad-Hoc Network is a special type of MANET or Mobile Ad-Hoc Network that is
designed specifically for communications between vehicles or V2V and vehicles to infrastructure or V2I. There
is a lot of studies and research that has been dedicated to study this technology due to its importance and
necessity in our life. The fact that each and every module presented must be tested thoroughly before putting it
into action, as there will be severe consequences in case of a system malfunction especially if it's a vehicular
design problem. However, seeing VANETS coming into reality becomes very close with the advancement of
IEEE 802.11p standard that is being dedicated to the DSRC or dedicated short range communication [1]. This
paper will discuss this technology emphasizing some of its applications, current limitations and future challenges
plus simulating a real traffic using SUMO and OpenStreetMap
EVALUATING LATENCY IN FIFTH-GENERATION VEHICLE-TO-EVERYTHING COMMUNICATIONS U...IJCNCJournal
The fifth-generation new radio technology (5G NR) introduces improved functions to the air interface. In
addition, the 5G NR non-standalone (NSA) will operate with long-term evolution, enabling vehicle-toeverything communications (V2X) for improved infotainment services. V2X includes four main classes of
communications: vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian devices, and vehicle-tonetwork. However, the stringent transmission frequency, latency, and throughput requirements of infotainment
applications constrain the transmitting packets of 5G-V2X-based NSA in highway scenarios. In this paper, the
latency is improved by preventing the physical layer of gNodeB and the user equipment (UE) from sending
redundant packets for service in a highway scenario. The proposed approach adopts an adaptive neuro-fuzzy
inference system (ANFIS), a powerful modeling technique based on artificial neural networks , and a fuzzy
inference system. The performance of ANFIS is compared with that of the traditional 5G V2X NSA architecture
in a simulation study using Voice over Internet Protocol (VoIP) traffic. The delays, throughputs, and packet
losses of both architectures are determined in radio link control (RLC) and VoIP applications. The switchmodes, signal-to-interference-noise ratios (SINRs), hybrid automatic repeat request (HARQ) error rate,
channel quality indicators (CQIs), served blocks, and transmission-state of gNodeB are computed for the two
architectures for device-to-device (D2D), uplink (UL) and downlink (DL) traffic directions. The simulation
results show comparable SINRs, CQIs, served blocks ,and switch modes in both scenarios, but the presented
ANFIS model significantly outperforms the traditional architecture in delay by 66% in D2D, 29% in UL, 25%
in DL, and packet loss by 21% in UL in RLC, the HARQ error rate by 9% in D2D, 30% in UL, 95% in DL,
transmission-state in gNodeB by 29%, and the delay by 4% for UEs, and frame loss by 90%for UE in VoIP.
Evaluating Latency in Fifth-Generation Vehicle-to-Everything communications U...IJCNCJournal
The fifth-generation new radio technology (5G NR) introduces improved functions to the air interface. In addition, the 5G NR non-standalone (NSA) will operate with long-term evolution, enabling vehicle-to-everything communications (V2X) for improved infotainment services. V2X includes four main classes of communications: vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian devices, and vehicle-to-network. However, the stringent transmission frequency, latency, and throughput requirements of infotainment applications constrain the transmitting packets of 5G-V2X-based NSA in highway scenarios. In this paper, the latency is improved by preventing the physical layer of gNodeB and the user equipment (UE) from sending redundant packets for service in a highway scenario. The proposed approach adopts an adaptive neuro-fuzzy inference system (ANFIS), a powerful modeling technique based on artificial neural networks ,and a fuzzy inference system. The performance of ANFIS is compared with that of the traditional 5G V2X NSA architecture in a simulation study using Voice over Internet Protocol (VoIP) traffic. The delays, throughputs, and packet losses of both architectures are determined in radio link control (RLC) and VoIP applications. The switch-modes, signal-to-interference-noise ratios (SINRs), hybrid automatic repeat request (HARQ) error rate, channel quality indicators (CQIs), served blocks, and transmission-state of gNodeB are computed for the two architectures for device-to-device (D2D), uplink (UL) and downlink (DL) traffic directions. The simulation results show comparable SINRs, CQIs, served blocks ,andswitchmodes in both scenarios, but the presented ANFIS model significantly outperforms the traditional architecture in delay by 66% in D2D, 29% in UL, 25% in DL, and packet loss by 21% in UL in RLC, the HARQ error rate by 9% in D2D, 30% in UL, 95% in DL, transmission-state in gNodeB by 29%, and the delay by 4% for UEs, and frame loss by 90%for UE in VoIP.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Security schemes based on conditional privacy-preserving vehicular ad hoc net...nooriasukmaningtyas
Recently, vehicular ad hoc networks (VANETs) have been garnering
significant inter-est from the people involved in transportation field.
Nowadays automotive manufactur-ers have already supplying vehicles with
multitude of road sensors that provides many useful characteristics. VANET
communication not only offers the drivers and passen-gers with the various
safety related services but also provides a wide range of valuable
applications. However, the inherent openness of the wireless communication
medium used by VANETs exposes vehicles to various security and privacy
issues. Researchers have proposed many security schemes to solve the issues
mentioned above for the widespread deployment of VANETs. However,
these schemes failed to fulfill all as-pects of security and privacy
requirements. Besides, these schemes have not provided the performance
parameters such as computation and communication costs. The pri-mary
emphasis of this paper is on the taxonomy of security schemes based
conditional privacy-preserving with respect to strengths and limitations.
Besides, a comparison be-tween these schemes related to the model of
security and privacy requirements, attacks, and performance parameters is
provided. Finally, this paper critically reviews the re-lated works by taking
into consideration the design and development of all VANETs security and
privacy schemes, this paper could serve as a guide and reference.
Vehicle-2-Vehicle Communication Based on Wireless Sensor NetworkjournalBEEI
Truck Platooning is a car innovation that permits gathering various trucks into a single element where one truck intently takes after the other that outcomes in an expanded street limit. This kind of detachment allows to a significant degree tight separations and synchronous driving between the vehicles. Our point is to plan and exhibit a self-ruling truck platooning framework given vehicle-to-vehicle (V2V) correspondence innovation. The structure utilises IEEE 802.15.4 remote convention joined with separation going sensors to enable vehicles inside the company to safely trade data progressively and naturally break and quicken in light of the lead truck. The rapid of remote correspondence permits to a significant degree tight separations and synchronous driving between the platooning vehicles.
A Broadcasting Scheme for Message Dissemination in VANETIJERA Editor
Vehicular Ad hoc Networks [VANET] is one of the fastest emerging technologies for research as there are many issues and challenges to be addressed by the researchers before the technology becomes commercialized. Vehicular communication systems developed largely by the growing interest in intelligent transportation systems [ITS]. Cooperative driving can improve safety and efficiency by enabling vehicles to exchange emergency messages to each other in the neighborhood and to assist driver in making proper decision to avoid vehicle collisions and congestion. Broadcast transmission is usually used for disseminating safety related information among vehicles. Message Broadcast over wireless networks poses many challenges due to link unreliability, hidden terminal, message redundancy, and broadcast storm, etc., which greatly degrade the network performance. In most of the emergency situations, there is less time to make a handshake with other nodes in the networks, as the emergency message is to be delivered fast and efficient. Broadcasting information is usually very costly and without limiting techniques this will result in serious data redundancy, contention and collisions. This work focuses on Broadcasting Scheme for Message Dissemination.
Technical Review on Different Applications, Challenges and Security in VANETPallavi Agarwal
Vehicular ad-hoc networks (VANETs) technology has turned out as a vital research field throughout the most recent couple of years. VANETs are the likely an impacting way to deal with giving security of driver and different applications for the activity conditions and additionally travelers. Being dynamic in nature, it created the network, according to the condition and requirement of the users and provides consistent communication between the vehicles. Due to its excessive advantages, it is highly susceptible to numerous attacks and security in VANET should be taken into consideration. This paper presented the security issues such as authenticity, integrity, availability, confidentiality, anonymity and non-repudiation to provide the secure communication between Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). Numerous research works have been done to recover the performance and security of this network. The fundamental point of this paper is the several security challenges and the applications of VANETs.
A heterogeneous short-range communication platform for Internet of Vehicles IJECEIAES
The automotive industry is rapidly accelerating toward the development of innovative industry applications that feature management capabilities for data and applications alike in cars. In this regard, more internet of vehicles solutions are emerging through advancements of various wireless medium access-control technologies and the internet of things. In the present work, we develop a short-range communication–based vehicular system to support vehicle communication and remote car control. We present a combined hardware and software testbed that is capable of controlling a vehicle’s start up, operation and several related functionalities covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino and Raspberry Pi 3, each of which individually controls certain functions to improve the overall vehicle control. The implementation of the heterogeneous communication module is based on the IEEE 802.11 and IEEE 802.15 medium access control technologies. Further, a control module on a smartphone was designed and implemented for efficient management. Moreover, we study the system connectivity performance by measuring various important parameters including the coverage distance, signal strength, download speed and latency. This study covers the use of this technology setup in different geographical areas over various time spans.
Towards Improving Road Safety Using Advanced Vehicular NetworksTELKOMNIKA JOURNAL
Vehicular Ad-hoc Networks (VANETs) are advanced network technologies applied to improve safety on roads and to offer suitable solutions for Intelligent Transportation Systems (ITS). The goal of VANETs is to assistdrivers and to act as a smart co-pilot that can alret about accidents and help avoiding them while prodivding high-end infotainment systems for both the driver and passengers. Consequently, VANETs can save millions of lives around the world, especially in Saudi Arabia, which has a very high rate of road accidents annualy. In this paper, we introduce and discuss VANETs, related routing protocols, challenging problems, and the existing solutions. This work is a part of a bigger project that aims to enhance VANETs technologies and to updapteITS to significantly promote road safety in general and Saudi Arabia’s roads in particular.
Cloud computing and the low power wide area network (LPWAN) network represent the key infrastructures for developing intelligent solutions based on the internet of things (IoT). However, the diversity of use cases and deployment scenarios of IoT in the different domains makes optimizing IoT-based cloud solutions a major challenge. The cloud solution’s cost increases with the increase in central processing unit (CPU) resources and energy consumption. The optimal use of edge material resources in industrial solutions will reduce the consumption of resources and thus optimize cloud infrastructure costs in terms of resources and energy consumption. The article presents the network and application architecture of an IoT monitoring solution based on cloud services. Then, we study the integration of IoT services based on application placement strategies on the fog cloud compared to the traditional centralized cloud strategy. Simulations evaluate the scenarios with the iFogSim simulator and the analyzed results compare the traditional strategy with the cloud-fog. The results show that cost and energy consumption in the cloud can be significantly reduced by processing the application at the end devices level with respect to the possible limit of CPU processing power for each IoT end device. Latency and network usage respect quality of service constraints in cloud-fog placement for this type of monitoring-oriented IoT application.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Coverage enhancements of vehicles users using mobile stations at 5G cellular ...nooriasukmaningtyas
High mobility requirements are one of the challenges face fifth-generation wireless (5G) cellular networks by providing acceptable wireless services to users traveling at speed up to 350 km/h. This paper presents a new scenario to increase the bit rate and coverage for passengers that use the vehicles for traveling through the installation a mobile station (MS) on these vehicles to provide a high-quality service to users. Based on signal to noise ratio (SNR’s) mathematical derivation and the outage probability of the user link, the proposed system is evaluated. Numerical results indicate an enhancement for users who received signal strength (RSS) from (-72 to -55) dBm and (15 to 38) Mbps in bit rate. Moreover, their number of users increased by proposed system adoption.
Vehicular Ad Hoc Networks (VANETs) are classified as a special application of mobile ad hoc networks (MANETs)
which promise the new possibilities to improve traffic efficiency, road safety driving convenience. By providing the safety and
non-safety applications and sharing the useful information through vehicle to vehicle (V2V) or vehicle to roadside (V2R)
communications to avoid accidents and provide reliable information to travellers, such hot issues seeks much attention of
researchers in this field. VANET and MANET having several common characteristics but VANET differ with applications,
architecture, challenges and data dissemination. The survey of routing protocols in VANETs is important and necessary issue for
smart ITS. The objective of this paper is to design an algorithm for the detection and correction of routing attacks made by
obstructive nodes in VANETS and also drawn the comparison between various metrics like Cost, Average Packet loss,
Throughput and Energy Consumed.
In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.
Agriculture has since become a major source of livelihood for Nigerians. It also accounts for over 85% of the total food consumed within her borders. The sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of food safety data, no standards in agricultural produce, non-adaptation to precision farming, and non-harmony via inventory trace supports. This study proposes blockchain-based trace-support in a continued effort to ensure food quality, consumer safety, and trading of food assets. It uses the radio frequency identification (RFID) sensor to register and track livestocks, farms/farmers, and abattoir processes as well as provisions a databank to trace livestock data. Results show the model adequately perform about 1,101 transactions per seconds with a response time of 0.21 s for queries and 0.28 s for https pages respectively for 2,500 users. Also, it yields a slightly longer time of 0.32 s for queries and 0.38 s for https pages respectively with an increased 5,000 users via the world-state as stored in the blockchain’s hyper-fabric ledger. Overall, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system.
EVALUATING LATENCY IN FIFTH-GENERATION VEHICLE-TO-EVERYTHING COMMUNICATIONS U...IJCNCJournal
The fifth-generation new radio technology (5G NR) introduces improved functions to the air interface. In
addition, the 5G NR non-standalone (NSA) will operate with long-term evolution, enabling vehicle-toeverything communications (V2X) for improved infotainment services. V2X includes four main classes of
communications: vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian devices, and vehicle-tonetwork. However, the stringent transmission frequency, latency, and throughput requirements of infotainment
applications constrain the transmitting packets of 5G-V2X-based NSA in highway scenarios. In this paper, the
latency is improved by preventing the physical layer of gNodeB and the user equipment (UE) from sending
redundant packets for service in a highway scenario. The proposed approach adopts an adaptive neuro-fuzzy
inference system (ANFIS), a powerful modeling technique based on artificial neural networks , and a fuzzy
inference system. The performance of ANFIS is compared with that of the traditional 5G V2X NSA architecture
in a simulation study using Voice over Internet Protocol (VoIP) traffic. The delays, throughputs, and packet
losses of both architectures are determined in radio link control (RLC) and VoIP applications. The switchmodes, signal-to-interference-noise ratios (SINRs), hybrid automatic repeat request (HARQ) error rate,
channel quality indicators (CQIs), served blocks, and transmission-state of gNodeB are computed for the two
architectures for device-to-device (D2D), uplink (UL) and downlink (DL) traffic directions. The simulation
results show comparable SINRs, CQIs, served blocks ,and switch modes in both scenarios, but the presented
ANFIS model significantly outperforms the traditional architecture in delay by 66% in D2D, 29% in UL, 25%
in DL, and packet loss by 21% in UL in RLC, the HARQ error rate by 9% in D2D, 30% in UL, 95% in DL,
transmission-state in gNodeB by 29%, and the delay by 4% for UEs, and frame loss by 90%for UE in VoIP.
Evaluating Latency in Fifth-Generation Vehicle-to-Everything communications U...IJCNCJournal
The fifth-generation new radio technology (5G NR) introduces improved functions to the air interface. In addition, the 5G NR non-standalone (NSA) will operate with long-term evolution, enabling vehicle-to-everything communications (V2X) for improved infotainment services. V2X includes four main classes of communications: vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian devices, and vehicle-to-network. However, the stringent transmission frequency, latency, and throughput requirements of infotainment applications constrain the transmitting packets of 5G-V2X-based NSA in highway scenarios. In this paper, the latency is improved by preventing the physical layer of gNodeB and the user equipment (UE) from sending redundant packets for service in a highway scenario. The proposed approach adopts an adaptive neuro-fuzzy inference system (ANFIS), a powerful modeling technique based on artificial neural networks ,and a fuzzy inference system. The performance of ANFIS is compared with that of the traditional 5G V2X NSA architecture in a simulation study using Voice over Internet Protocol (VoIP) traffic. The delays, throughputs, and packet losses of both architectures are determined in radio link control (RLC) and VoIP applications. The switch-modes, signal-to-interference-noise ratios (SINRs), hybrid automatic repeat request (HARQ) error rate, channel quality indicators (CQIs), served blocks, and transmission-state of gNodeB are computed for the two architectures for device-to-device (D2D), uplink (UL) and downlink (DL) traffic directions. The simulation results show comparable SINRs, CQIs, served blocks ,andswitchmodes in both scenarios, but the presented ANFIS model significantly outperforms the traditional architecture in delay by 66% in D2D, 29% in UL, 25% in DL, and packet loss by 21% in UL in RLC, the HARQ error rate by 9% in D2D, 30% in UL, 95% in DL, transmission-state in gNodeB by 29%, and the delay by 4% for UEs, and frame loss by 90%for UE in VoIP.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Security schemes based on conditional privacy-preserving vehicular ad hoc net...nooriasukmaningtyas
Recently, vehicular ad hoc networks (VANETs) have been garnering
significant inter-est from the people involved in transportation field.
Nowadays automotive manufactur-ers have already supplying vehicles with
multitude of road sensors that provides many useful characteristics. VANET
communication not only offers the drivers and passen-gers with the various
safety related services but also provides a wide range of valuable
applications. However, the inherent openness of the wireless communication
medium used by VANETs exposes vehicles to various security and privacy
issues. Researchers have proposed many security schemes to solve the issues
mentioned above for the widespread deployment of VANETs. However,
these schemes failed to fulfill all as-pects of security and privacy
requirements. Besides, these schemes have not provided the performance
parameters such as computation and communication costs. The pri-mary
emphasis of this paper is on the taxonomy of security schemes based
conditional privacy-preserving with respect to strengths and limitations.
Besides, a comparison be-tween these schemes related to the model of
security and privacy requirements, attacks, and performance parameters is
provided. Finally, this paper critically reviews the re-lated works by taking
into consideration the design and development of all VANETs security and
privacy schemes, this paper could serve as a guide and reference.
Vehicle-2-Vehicle Communication Based on Wireless Sensor NetworkjournalBEEI
Truck Platooning is a car innovation that permits gathering various trucks into a single element where one truck intently takes after the other that outcomes in an expanded street limit. This kind of detachment allows to a significant degree tight separations and synchronous driving between the vehicles. Our point is to plan and exhibit a self-ruling truck platooning framework given vehicle-to-vehicle (V2V) correspondence innovation. The structure utilises IEEE 802.15.4 remote convention joined with separation going sensors to enable vehicles inside the company to safely trade data progressively and naturally break and quicken in light of the lead truck. The rapid of remote correspondence permits to a significant degree tight separations and synchronous driving between the platooning vehicles.
A Broadcasting Scheme for Message Dissemination in VANETIJERA Editor
Vehicular Ad hoc Networks [VANET] is one of the fastest emerging technologies for research as there are many issues and challenges to be addressed by the researchers before the technology becomes commercialized. Vehicular communication systems developed largely by the growing interest in intelligent transportation systems [ITS]. Cooperative driving can improve safety and efficiency by enabling vehicles to exchange emergency messages to each other in the neighborhood and to assist driver in making proper decision to avoid vehicle collisions and congestion. Broadcast transmission is usually used for disseminating safety related information among vehicles. Message Broadcast over wireless networks poses many challenges due to link unreliability, hidden terminal, message redundancy, and broadcast storm, etc., which greatly degrade the network performance. In most of the emergency situations, there is less time to make a handshake with other nodes in the networks, as the emergency message is to be delivered fast and efficient. Broadcasting information is usually very costly and without limiting techniques this will result in serious data redundancy, contention and collisions. This work focuses on Broadcasting Scheme for Message Dissemination.
Technical Review on Different Applications, Challenges and Security in VANETPallavi Agarwal
Vehicular ad-hoc networks (VANETs) technology has turned out as a vital research field throughout the most recent couple of years. VANETs are the likely an impacting way to deal with giving security of driver and different applications for the activity conditions and additionally travelers. Being dynamic in nature, it created the network, according to the condition and requirement of the users and provides consistent communication between the vehicles. Due to its excessive advantages, it is highly susceptible to numerous attacks and security in VANET should be taken into consideration. This paper presented the security issues such as authenticity, integrity, availability, confidentiality, anonymity and non-repudiation to provide the secure communication between Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). Numerous research works have been done to recover the performance and security of this network. The fundamental point of this paper is the several security challenges and the applications of VANETs.
A heterogeneous short-range communication platform for Internet of Vehicles IJECEIAES
The automotive industry is rapidly accelerating toward the development of innovative industry applications that feature management capabilities for data and applications alike in cars. In this regard, more internet of vehicles solutions are emerging through advancements of various wireless medium access-control technologies and the internet of things. In the present work, we develop a short-range communication–based vehicular system to support vehicle communication and remote car control. We present a combined hardware and software testbed that is capable of controlling a vehicle’s start up, operation and several related functionalities covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino and Raspberry Pi 3, each of which individually controls certain functions to improve the overall vehicle control. The implementation of the heterogeneous communication module is based on the IEEE 802.11 and IEEE 802.15 medium access control technologies. Further, a control module on a smartphone was designed and implemented for efficient management. Moreover, we study the system connectivity performance by measuring various important parameters including the coverage distance, signal strength, download speed and latency. This study covers the use of this technology setup in different geographical areas over various time spans.
Towards Improving Road Safety Using Advanced Vehicular NetworksTELKOMNIKA JOURNAL
Vehicular Ad-hoc Networks (VANETs) are advanced network technologies applied to improve safety on roads and to offer suitable solutions for Intelligent Transportation Systems (ITS). The goal of VANETs is to assistdrivers and to act as a smart co-pilot that can alret about accidents and help avoiding them while prodivding high-end infotainment systems for both the driver and passengers. Consequently, VANETs can save millions of lives around the world, especially in Saudi Arabia, which has a very high rate of road accidents annualy. In this paper, we introduce and discuss VANETs, related routing protocols, challenging problems, and the existing solutions. This work is a part of a bigger project that aims to enhance VANETs technologies and to updapteITS to significantly promote road safety in general and Saudi Arabia’s roads in particular.
Cloud computing and the low power wide area network (LPWAN) network represent the key infrastructures for developing intelligent solutions based on the internet of things (IoT). However, the diversity of use cases and deployment scenarios of IoT in the different domains makes optimizing IoT-based cloud solutions a major challenge. The cloud solution’s cost increases with the increase in central processing unit (CPU) resources and energy consumption. The optimal use of edge material resources in industrial solutions will reduce the consumption of resources and thus optimize cloud infrastructure costs in terms of resources and energy consumption. The article presents the network and application architecture of an IoT monitoring solution based on cloud services. Then, we study the integration of IoT services based on application placement strategies on the fog cloud compared to the traditional centralized cloud strategy. Simulations evaluate the scenarios with the iFogSim simulator and the analyzed results compare the traditional strategy with the cloud-fog. The results show that cost and energy consumption in the cloud can be significantly reduced by processing the application at the end devices level with respect to the possible limit of CPU processing power for each IoT end device. Latency and network usage respect quality of service constraints in cloud-fog placement for this type of monitoring-oriented IoT application.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Coverage enhancements of vehicles users using mobile stations at 5G cellular ...nooriasukmaningtyas
High mobility requirements are one of the challenges face fifth-generation wireless (5G) cellular networks by providing acceptable wireless services to users traveling at speed up to 350 km/h. This paper presents a new scenario to increase the bit rate and coverage for passengers that use the vehicles for traveling through the installation a mobile station (MS) on these vehicles to provide a high-quality service to users. Based on signal to noise ratio (SNR’s) mathematical derivation and the outage probability of the user link, the proposed system is evaluated. Numerical results indicate an enhancement for users who received signal strength (RSS) from (-72 to -55) dBm and (15 to 38) Mbps in bit rate. Moreover, their number of users increased by proposed system adoption.
Vehicular Ad Hoc Networks (VANETs) are classified as a special application of mobile ad hoc networks (MANETs)
which promise the new possibilities to improve traffic efficiency, road safety driving convenience. By providing the safety and
non-safety applications and sharing the useful information through vehicle to vehicle (V2V) or vehicle to roadside (V2R)
communications to avoid accidents and provide reliable information to travellers, such hot issues seeks much attention of
researchers in this field. VANET and MANET having several common characteristics but VANET differ with applications,
architecture, challenges and data dissemination. The survey of routing protocols in VANETs is important and necessary issue for
smart ITS. The objective of this paper is to design an algorithm for the detection and correction of routing attacks made by
obstructive nodes in VANETS and also drawn the comparison between various metrics like Cost, Average Packet loss,
Throughput and Energy Consumed.
In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.
Agriculture has since become a major source of livelihood for Nigerians. It also accounts for over 85% of the total food consumed within her borders. The sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of food safety data, no standards in agricultural produce, non-adaptation to precision farming, and non-harmony via inventory trace supports. This study proposes blockchain-based trace-support in a continued effort to ensure food quality, consumer safety, and trading of food assets. It uses the radio frequency identification (RFID) sensor to register and track livestocks, farms/farmers, and abattoir processes as well as provisions a databank to trace livestock data. Results show the model adequately perform about 1,101 transactions per seconds with a response time of 0.21 s for queries and 0.28 s for https pages respectively for 2,500 users. Also, it yields a slightly longer time of 0.32 s for queries and 0.38 s for https pages respectively with an increased 5,000 users via the world-state as stored in the blockchain’s hyper-fabric ledger. Overall, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system.
Diabetic retinopathy (DR) is one of the most common causes of blindness. The necessity for a robust and automated DR screening system for regular examination has long been recognized in order to identify DR at an early stage. In this paper, an embedded DR diagnosis system based on convolutional neural networks (CNNs) has been proposed to assess the proper stage of DR. We coupled the power of CNN with transfer learning to design our model based on state-of-the-art architecture. We preprocessed the input data, which is color fundus photography, to reduce undesirable noise in the image. After training many models on the dataset, we chose the adopted ResNet50 because it produced the best results, with a 92.90% accuracy. Extensive experiments and comparisons with other research work show that the proposed method is effective. Furthermore, the CNN model has been implemented on an embedded target to be a part of a medical instrument diagnostic system. We have accelerated our model inference on a field programmable gate array (FPGA) using Xilinx tools. Results have confirmed that a customized FPGA system on chip (SoC) with hardware accelerators is a promising target for our DR detection model with high performance and low power consumption.
As many countries experience the emergence of new waves of Covid-19, many governments around the world have reminded their citizens of the need for an engaging intervention that could improve compliance with Covid-19 safe behaviors using the media general public or social media. In the face of the serious threat of Covid-19, immunity issues are currently the subject of various research and studies. A promising approach is to use video game culture to educate and train citizens to healthily adopt eating habits to strengthen the immune system. The objective of this study is to develop a prototype of a serious game (SG) on how to strengthen the immune defenses in order to be able to fight a coronavirus infection and to constitute an antivirus barrier. After defining the learning objectives by interviewing the stakeholders, we searched the scientific literature to establish the relevant theoretical bases. The learning contents have been validated by biology teachers. The learning mechanisms were then determined based on the learning objectives. The obtained experimental results show that 92% of the participants in the study have appreciated the quality of the scenario and the way in which the concept of interaction between the different game elements was presented.
The need for automated speech recognition has expanded as a result of significant industrial expansion for a variety of automation and humanmachine interface applications. The speech impairment brought on by communication disorders, neurogenic speech disorders, or psychological speech disorders limits the performance of different artificial intelligencebased systems. The dysarthric condition is a neurogenic speech disease that restricts the capacity of the human voice to articulate. This article presents a comprehensive survey of the recent advances in the automatic dysarthric speech recognition (DSR) using machine learning (ML) and deep learning (DL) paradigms. It focuses on the methodology, database, evaluation metrics, and major findings from the study of previous approaches. From the literature survey it provides the gaps between exiting work and previous work on DSR and provides the future direction for improvement of DSR. The performance of the various machine and DL schemes is evaluated for the DSR on UASpeech dataset based on accuracy, precision, recall, and F1- score. It is observed that the DL based DSR schems outperforms the ML based DSR schemes.
The router is a network device that is used to connect subnetwork and packet-switched networking by directing the data packets to the intended IP addresses. It succeeds the traffic between different systems and allows several devices to share the internet connection. The router is applicable for the effective commutation in system on chip (SoC) modules for network on chip (NoC) communication. The research paper emphasizes the design of the two dimensional (2D) router hardware chip in the Xilinx integrated system environment (ISE) 14.7 software and further logic verification using the data packets transmitted from all input/output ports. The design evaluation is done based on the pre-synthesis device utilization summary relating to different field programmable gate array (FPGA) boards such as Spartan-3E (XC3S500E), Spartan-6 (XC6SLX45), Virtex-4 (XC4VFX12), Virtex-5 (XC5VSX50T), and Virtex-7 (XC7VX550T). The 64-bit data logic is verified on the different ports of the router configuration in the Xilinx and Modelsim waveform simulator. The Virtex-7 has proven the fast-switching speed and optimal hardware parameters in comparison to other FPGAs.
In this work, an internet of things (IoT) sensing and monitoring box has been developed. The proposed low-cost system is a portable device for smart buildings to measure vibrations, monitor, and control noise caused by the industrial machines. We will present an instrument and a method to measure the vibration and tilt of a mechanical system (air conditioner). The primary goal is to create a signal acquisition and monitoring system that is both userfriendly and affordable, while also delivering exceptional precision. The key concept is centered around acquiring and processing signals through the Raspberry Pi. We will use for the first time as an application, which does not exist before, a conversion method to control and monitor remotely the noise generated by the machines. Once the noise reaches a high value or the air conditioner is too much tilted, the system sends an alert in the form of an email. We will use the Python language to acquire and process the signal and send the alerts. The proposed approach is straightforward to implement, and the obtained results demonstrate a high level of accuracy that is consistent with the existing literature.
The use of a convolutional neural network (CNN) to analyze and classify electroencephalogram (EEG) signals has recently attracted the interest of researchers to identify epileptic seizures. This success has come with an enormous increase in the computational complexity and memory requirements of CNNs. For the sake of boosting the performance of CNN inference, several hardware accelerators have been proposed. The high performance and flexibility of the field programmable gate array (FPGA) make it an efficient accelerator for CNNs. Nevertheless, for resource-limited platforms, the deployment of CNN models poses significant challenges. For an ease of CNN implementation on such platforms, several tools and frameworks have been made available by the research community along with different optimization techniques. In this paper, we proposed an FPGA implementation for an automatic seizure detection approach using two CNN models, namely VGG-16 and ResNet-50. To reduce the model size and computation cost, we exploited two optimization approaches: pruning and quantization. Furthermore, we presented the results and discussed the advantages and limitations of two implementation alternatives for the inference acceleration of quantized CNNs on Zynq-7000: an advanced RISC machine (ARM) software implementation-based ARM, NN, software development kit (SDK) and a software/hardware implementation-based deep learning processor unit (DPU) accelerator and DNNDK toolkit.
A number of benefits have been reported for computer-based assessments over traditional paper-based exams, both in terms of IT support for question development, reduced distribution and test administration costs, and automated support. Possible for the ranking. However, existing computerized assessment systems do not provide all kinds of questions, namely open questions that require writing solutions. To overcome the challenges of the existing, the objective of this work is to achieve an intelligent evaluation system (IES) responding to the problems identified, and which adapts to the different types of questions, especially open-ended questions of which the answer requires sentence writing or programming.
Convolutional neural networks (CNN) trained using deep learning (DL) have advanced dramatically in recent years. Researchers from a variety of fields have been motivated by the success of CNNs in computer vision to develop better CNN models for use in other visually-rich settings. Successes in image classification and research have been achieved in a wide variety of domains throughout the past year. Among the many popularized image classification techniques, the detection of plant leaf diseases has received extensive research. As a result of the nature of the procedure, image quality is often degraded and distortions are introduced during the capturing of the image. In this study, we look into how various CNN models are affected by distortions. Corn-maze leaf photos from the 4,188-image corn or maize leaf Dataset (split into four categories) are under consideration. To evaluate how well they handle noise and blur, researchers have deployed pre-trained deep CNN models like visual geometry group (VGG), InceptionV3, ResNet50, and EfficientNetB0. Classification accuracy and metrics like as recall and f1-score are used to evaluate CNN performance.
In this research, we present a low phase noise (PN) and wide tuning range 175 GHz inductors and capacitors (LC) voltage-controlled oscillator (VCO) based on a differential Colpitts oscillator that was designed using a 0.13 μm bipolar complementary metal oxide semiconductor (BiCMOS) and simulated. The square of the tank Q-factor and the square of the oscillation amplitude were both maximized to reduce PN. With an extensive examination of parasitic, mathematical analysis of load impedances, and implementation of differential design, the PN was reduced, and the output power was enhanced. Using a supply voltage of 1.6 V, the VCO consumes 41.9 mA, resulting in a total power usage of 67 mW to prevent undesirable PN deterioration, an inter-stage LC filter at the VCO-buffer interface increases the swing at the buffer input. To make a better output, a buffer is used to isolate the load from the VCO core. In addition, the VCO has a high linearity and the overall, the VCO presented in this study demonstrates excellent performance and has the potential to be used in a wide range of applications that require a high-performance, low-power VCO.
Diseases in edible and industrial plants remains a major concern, affecting producers and consumers. The problem is further exacerbated as there are different species of plants with a wide variety of diseases that reduce the effectiveness of certain pesticides while increasing our risk of illness. A timely, accurate and automated detection of diseases can be beneficial. Our work focuses on evaluating deep learning (DL) approaches using transfer learning to automatically detect diseases in plants. To enhance the capabilities of our approach, we compiled a novel image dataset containing 87,570 records encompassing 32 different plants and 74 types of diseases. The dataset consists of leaf images from both laboratory setups and cultivation fields, making it more representative. To the best of our knowledge, no such datasets have been used for DL models. Four pretrained computer vision models, namely VGG-16, VGG-19, ResNet-50, and ResNet-101 were evaluated on our dataset. Our experiments demonstrate that both VGG-16 and VGG-19 models proved more efficient, yielding an accuracy of approximately 86% and a f1-score of 87%, as compared to ResNet-50 and ResNet-101. ResNet-50 attains an accuracy and a f1-score of 46.9% and 45.6%, respectively, while ResNet-101 reaches an accuracy of 40.7% and a f1-score of 26.9%.
In this proposed work, we identified the significant research issues on lung cancer risk factors. Capturing and defining symptoms at an early stage is one of the most difficult phases for patients. Based on the history of patients records, we reviewed a number of current research studies on lung cancer and its various stages. We identified that lung cancer is one of the significant research issues in predicting the early stages of cancer disease. This research aimed to develop a model that can detect lung cancer with a remarkably high level of accuracy using the deep learning approach (convolution neural network). This method considers and resolves significant gaps in previous studies. We compare the accuracy levels and loss values of our model with VGG16, InceptionV3, and Resnet50. We found that our model achieved an accuracy of 94% and a minimum loss of 0.1%. Hence physicians can use our convolution neural network models for predicting lung cancer risk factors in the real world. Moreover, this investigation reveals that squamous cell carcinoma, normal, adenocarcinoma, and large cell carcinoma are the most significant risk factors. In addition, the remaining attributes are also crucial for achieving the best performance.
Wirelessly based security applications have exploded as a result of modern technology. To build and/or implement security access control systems, many types of wireless communication technologies have been deployed. quick response (QR code) is a contactless technology that is extensively utilised in a variety of sectors, including access control, library book tracking, supply chains, and tollgate systems, among others. This paper combines QR code technology with Arduino and Python to construct an automated QR code-based access management system. After detecting a QR code, the QR scanner at the entry collects and compares the user's unique identifier (UID) with the UID recorded in the system. The results show that this system is capable of granting or denying access to a protected environment in a timely, effective, and reliable way. Security systems can protect physical and intellectual property by preventing unauthorized persons from entering the area. Many door locks, such as mechanical and electrical locks, were created to meet basic security needs but it also helps to create a data files structure of the authorized persons.
Localization is a critical concern in many wireless sensor network (WSN) applications. Furthermore, correct information regarding the geographic placements of nodes (sensors) is critical for making the collected data valuable and relevant. Because of their benefits, such as simplicity and acceptable accuracy, the based connectivity algorithms attempt to localize multi-hop WSN. However, due to environmental factors, the precision of localisation may be rather low. This publication describes an extreme learning machine (ELM) technique for minimizing localization error in range-free WSN. In this paper, we propose a Cascade-ELM to increase localization accuracy in range-free WSNs. We tested the proposed approaches in a variety of multi-hop WSN scenarios. Our research focused on an isotropic and irregular environment. The simulation results show that the proposed Cascade-ELM algorithm considerably improves localization accuracy when compared to previous algorithms derived from smart computing approaches. When compared to previous work, isotropic environments show improved localization results.
The study evaluated interference in a dense heterogeneous network using third-generation universal mobile telecommunication systems (UMTS) and fourth-generation long term evolution (LTE) networks LTE. The UMTs/LTE heterogeneous network determines the level of interference when the two communication systems coexist and how to improve the network by migrating from UMTs to LTE, which has a faster download speed and larger capacity. Techno lite 8 on third generation (3G) and Infinix Pro 6 on fourth generation (4G) were used to measure network the received signal strength (RSS) during site investigation. UE interference was detected and traced using a spectrum analyzer. UMTS and LTE path loss exponents are 2.6 and 3.2. Shannon's capacity theorem calculated LTE and UMTS capacity. When signal to interference and noise ratio (SINR) was used as a quality of service (QoS) indicator, MATLAB channel capacity plots did not match Shannon's due to neighboring interference. UMTS had an R2 of 0.54 and LTE 0.57 for the Shannon channel capacity equation. Adjacent channel interference (ACI) user devices reduce network capacity, lowering QoS for other customers.
The course activity log is where a learning management system (LMS) like Moodle keeps track of the various learning activities. The instructor may directly examine the log or use more complex method such as data mining to conduct a quicker and more in-depth examination of the student's behaviors. Most previous studies on analyzing this log data rely on predictive analysis. Instead of predictive analysis, this study investigates cluster analysis and association analysis. Cluster analysis based on k-means++ is utilized to organize students into groups, given their engagement in the learning course module. Association analysis based on apriori is utilized to extract the relationships between various student activities. A dashboard presentation of the findings is provided to facilitate clearer comprehension. Based on the analysis findings, it can be concluded that the structure of the student cluster is medium. In contrast, the association between student activities is positively correlated and well-balanced. The subjective review of the dashboard reveals that the visualization is already sufficient, but there are some recommendations for making it even better.
The software-defined network (SDN) controller adds and removes the contents of the flow table through secure channels to determine how packets are processed and how the flow table is managed. The controller pays attention to network intelligence and becomes the middle part, where the network manages the transfer data of the aircraft delivered via the OpenFlow (OF) switch. To this end, the controller provides an interface for managing, controlling, and managing this switch flow table. Run tests to calculate controller throughput and latency levels and test using the cbance tool, which can test transmission control protocol (TCP) and user datagram protocol (UDP) protocols. The tests are run by forcing the controller to run at maximum without any additional settings (default settings) in order to use the correct information about the controller’s capabilities. Because of this need, you need to test the performance of your controller. In this study, the tests were run on three popular controllers. Test results show that flowed controllers are more stable than open network operating dystem (ONOS) and open daylight (ODL) controllers in managing switch and host loads.
This study examined the influence of electronic government (e-government) implementation for the Ministry of Transport on fulfilling Saudi vision 2030 by transforming the Kingdom of Saudi Arabia (KSA) into a logistics center linking three continents. Saudi vision 2030 aims to cut transportation costs by improving infrastructure, shorten importing and exporting times by streamlining and automating operations, and increase supply chain transparency through sector reform. Implementing e-government would improve government services and engagement through information and communication technology (ICT). This article focuses on four primary areas: i) making KSA a logistics center; ii) increasing the chance of living throughout the Kingdom; and iii) promoting long-term financial sustainability. The study is founded on the idea that logistics is a crucial component for competitive advantage and transportation (by land, sea, or air) is a logistical sub-process for Saudi enterprises that benefit from transport networks similar to the best in the world. The Kingdom's strategic location at the junction of three continents gives its transport sector a geographical competitive advantage that provides access to important emerging markets and critical sea lanes. Despite the optimistic future of the transport and logistics industries in KSA, some important hurdles must be overcome.
Chronic disease (CD) such as kidney disease and causes severe challenging issues to the people all around the world. Chronic kidney disease (CKD) and diabetes mellitus (DM) are considered in this paper. Predicting the diseases in earlier stage, gives better preventive measures to the people. Healthcare domain leads to tremendous cost savings and improved health status of the society. The main objective of this paper is to develop an algorithm to predict CKD occurrence using machine learning (ML) technique. The commonly used classification algorithms namely logistic regression (LR), random forest (RF), conditional random forest (CRF), and recurrent neural networks (RNN) are considered to predict the disease at an earlier stage. The proposed algorithm in this paper uses medical code data to predict disease at an earlier stage.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
1. International Journal of Informatics and Communication Technology (IJ-ICT)
Vol. 12, No. 1, April 2023, pp. 54~61
ISSN: 2252-8776, DOI: 10.11591/ijict.v12i1.pp54-61 54
Journal homepage: http://ijict.iaescore.com
Comparative performance study of HC-12, nRF24L01, and
XBee for vehicular communication
Sumendra Yogarayan1
, Siti Fatimah Abdul Razak1
, Mohd. Fikri Azli Abdullah1
, Afizan Azman2
,
Vethanayagi Arultas1
, Suneetha Sri Raman1
1
Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia
2
School of Computing Science, Faculty of Innovation and Technology, Taylors University, Subang Jaya, Malaysia
Article Info ABSTRACT
Article history:
Received May 21, 2021
Revised Jun 10, 2022
Accepted Aug 30, 2022
In recent times, the volume of traffic congestion has been rapidly growing
on roads. These days the necessity of having safe transportation and journey
is essential. Thus, vehicle communication could be a possible solution to
enhance safe transit. Vehicular communications provide a wide range of
applications with different characteristics, namely vehicle and vehicle (V2V)
communications. Every year, traffic accidents kill many people worldwide,
and many people have been injured. V2V communication enables vehicles
to communicate with each other to provide safety and convenience to
drivers. Therefore, this paper explores a direction to develop a conceptual
approach to V2V communication with HC-12, nRF24L01, and XBee. The
study aims to analyze and evaluate the communication range that may
contribute to the future road transportation system.
Keywords:
Distance
HC-12
nRF24L01
Vehicle communication
XBee This is an open access article under the CC BY-SA license.
Corresponding Author:
Sumendra Yogarayan
Faculty of Information Science and Technology, Multimedia University
Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia
Email: sumendra@mmu.edu.my
1. INTRODUCTION
Road crashes kill many people in the world each year, and many more people are injured. The
primary reason for these accidents is a limitation due to situations on the road, which may be due to the brake
failure, sudden standstill or distance blackness [1], [2]. Furthermore, a delay in the driver's response to events
on the roadway could lead to unavoidable consequences [3], [4]. Road safety is often improved to ensure that
drivers can see the circumstances coming along the road. Hence, this would be possible if the vehicles were
communicating with each other. Vehicle and vehicle (V2V) communication is becoming a reality and will
provide various services for safety and efficiency [5], [6]. In addition, V2V has demonstrated that it can be
incorporated into current designed automotive applications. The exchange of information on vehicle mobility
and the state of the road between vehicles plays a significant role in the safety of drivers and passengers. A
driver can receive information about road conditions and vehicle speeds in the surrounding area in a
particular context. This helps the vehicle make better decisions about vehicle control and route.
In another context, when vehicles communicate in real-time, the driver can avoid potential crashes
by changing the speed based on the speed of the nearby vehicle [7]–[9]. Therefore, this paper explores the
communications platform used between vehicles with HC-12, nRF24L01, and XBee. This paper is organised
as follows: i) section 2 elaborates on the mechanism of the three modules and related works; ii) the
experimental work and outcome are shown in section 3; and iii) in the last section, the conclusion was
highlighted.
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2. RELATED WORKS
The HC-12 is a state-of-the-art semi-duplex wireless mode that provides a frequency spectrum of
433.4 to 473.0 MHz. The module is integrated and would use 100 channels at 400 kHz measurement. The
maximum module transmitting power is 100 MW, the receivable sensitivity is at a baud rate of 9,600 in the
air with -112 dBm, and the communication distance is less than 1,000 meters through open space. The low
data rate makes it possible to reach the most rapid communication ranges. There are three types of operation,
such as FU1, FU2, and FU3, which can be customised to the various requirements. For energy-saving modes,
FU1 and FU2 apply, while for maximum power mode, FU3 is suitable [10]–[14]. There are several studies of
the HC-12 modules for various purposes, as shown in Table 1.
Table 1. HC-12 related studies
Author Purpose Contribution
[15] Intelligent lane clearance and collision
avoidance system
Analyse on warning system to a vehicle when the vehicle crossed the permitted
limits
[16] Automatic vehicle overtaking system Analyse the phase delay of a propagating wave between two receiver antennas
[17] Safety and security of coal mine workers Analyse different parameters and take actions to mitigate all hazards
[18] Collision detection robot car model Analyse collision avoidance and maintain a safe distance between cars
[19] Vehicle platooning prototype car model Analyse predictive controller and navigation algorithms in longitudinal and path
control
[20] Vehicle to vehicle communication Analyse to attenuate vehicle noise to some degree and reduce vehicle horn
[21] Traffic signal control system Analyse an efficient route with a traffic light for emergency vehicles
[22] Vehicle speed proposition system Analyse to reduce accidents and warn drivers of the speed limit at high accident
zones
[23] Collision prevention and warning system Analyse to reduce collision and damage in circumstances of accidents
[24] Motorcyclist intelligent helmet Analyse to decrease violation by riders of traffic rules and cause accidents
[25] Smart motorcyclists protection system Analyse to reduce road accidents by riders under the influence of alcohol
[26] Toll gate system Analyse to apply contactless transaction overcoming the queue.
[27] Electric vehicle telemetry data system Analyse to monitor and acquire onboard telemetry data of the electric vehicle.
[28] Street light energy-saving tool Analyse to minimise energy consumption and reduce maintenance of street lights
[29] Accident location and traffic management
system
Analyse to convey a message to the rescue team in the circumstance of road
accidents
Generally, nRF24L01is a transmitter-receiver module that transmits and receives data on a specific
channel frequency. In addition, they should be on the same channel for two or more transmitter-receiver
modules to communicate. This channel can vary from 2.4 to 2.525 GHz within the 2.4 GHz
(2,400-2,525 MHz) industrial, scientific and medical (ISM) band. Each channel has a bandwidth of less than
1 MHz and 125 available channels. For instance, the nRF24L01 module also can use 125 different channels
and has a network of 125 independent modules in a location [30]–[34]. Several studies of the nRF24L01
modules are used for various purposes, as shown in Table 2.
Table 2. nRF24L01 related studies
Author Purpose Contribution
[35] Temperature measuring system Analyse transmitting temperature information in the event of exceeded set value
[36] Multipurpose radio-controlled car Analyse a transmitter unit in terms of reception accuracy and transmission
exactness
[37] Vehicle to V2V to infrastructure
communication system
Analyse to alert of potential hazards or violate action made by drivers
[38] Temperature and humidity sensing Analyse to evaluate the power efficiency and reliability of communication
[39] Multipurpose wireless sensing Analyse different approach contexts for possible long operation
[40] Wireless control car movement Analyse to improve the efficiency of transportation through wireless
communication
[41] Data collection box tool Analyse temperature values at different environments and alarm abnormal
temperatures
[42] Quaternion based wireless data transfer Analyse real-time transmission and acquisition of sensor data
[43] Automatic gate control system Analyse to avoid the head-on and collision that occur by human negligence
[44] Automatic street light control system Analyse to reduce the energy consumption of transmitting information to a base
station
[45] Inter vehicle collision avoidance system Analyse prototype cars to avoid a collision at road accidents areas
[46] Inter vehicle alert system Analyse vehicle communication for reducing accidents due to drivers negligence
[47] An autonomous vehicle surveillance system Analyse transmitting data at different road conditions and speeds
[48] Motorcyclist smart helmet and blind-spot
detection
Analyse on warning motorcyclists of potential hazards that can decrease the
probability of road accidents
[49] Motorcyclist smart helmet accident detection Analyse sending messages to immediate family members if accidents have
occurred.
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XBee modules are wireless communication modules that are constructed following the Zigbee
standard. XBee is an RF module transceiver that uses the IEEE 802.15.4 protocol. The XBee is a modular
product design that makes rolling out wireless technology simple and cost-effective. It can be used as a serial
replacement or placed in a control mode and configured for various broadcast and mesh network options. The
module provides connectivity solutions to wireless endpoints of built-in devices. Xbee has a 2 dBm beam
with a sensitivity minimum of -96 dBm. The XBee and XBee-pro radio frequency (RF) modules are built-in
solutions providing wireless connectivity solutions. The 3-pin RF modules can be connected directly to the
controller, which does not need an encoder or decoder [50]–[54]. Several studies have used XBee for various
purposes, as shown in Table 3.
Table 3. XBee related studies
Author Purpose Contribution
[55] Wireless sensor network for environmental
monitoring
Analyse the transmission of data in real-time deployment
[56] Wireless sensor network for aquaculture monitoring Analyse temperature and manage automatic turn on a fan for shrimp pool
[57] Early detection system for fire disaster Analyse on transmitting data in real-time to a specific place
[58] Patients heart monitoring system Analyse monitoring patient health data in real-time
[59] Real-time vehicle communication tool Analyse the communication range of vehicles to transmit data
[60] Wireless sensor network for environmental
monitoring
Analyse on monitoring real-time data and display through multiple
platforms
[61] Wireless environmental control for smart mushroom
house
Analyse the dampness of the air and the level of CO2
inside the area
[62] Wireless control robot for multiple sensors Analyse the measurement and display on a human interaction machine
[63] Cost-effective vehicle tracking system Analyse tracking vehicles in various environments regardless of obstacles.
[64] Wireless sensor network for environmental
monitoring
Analyse transmitting data in real-time and observe the power consumption
[65] Smart parking infrastructure system Analyse on detecting the presence of a vehicle and transmit data to the
gateway
[66] Driver assistance system Analyse on automation process of the driving system to avoid drivers'
negligence
[67] Automatic traffic control for an ambulance Analyse on determining the traffic congestion and provide smooth route
direction
[68] Intelligent traffic light system for ambulance clearanceAnalyse ambulance vehicle movement that can control traffic light flow
[69] Traffic management system for emergency vehicle Analyse controlling traffic lights for smooth flow of emergency vehicles
3. EXPERIMENT AND DISCUSSION
As illustrated in the following subsection, several hardware components were required to interface
with the modules in this experiment.
3.1. Hardware
The prototype is designed using Arduino Uno integrated separately with three modules such as
HC-12, nRF24L01 and XBee. The ultrasonic sensor works along with the modules to detect the range of
vehicles for a potential collision. Any alert is indicated in the form of an audible buzzer and visible light
emitting diode (LED). The equipment component specifications are presented in Table 4.
Table 4. Equipment/components specifications
Components Units
Arduino Uno 9
HC-12 3
nRF24L01 3
XBee 3
Ultrasonic sensor HC-SR04 9
Buzzer 9
LED 9
3.2. Settings and implementation
The performance analysis of three modules is restricted to a controlled environment, as shown in
Figure 1. In accordance with the information presented in the preceding section, each testing setting has been
established appropriately with the modules. The initial configurations would use HC-12, then nRF24L01, and
finally XBee. Figure 2 shows the initial prototype designed to be tested in the given controlled environment
settings.
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Figure 1. Environment settings
Figure 2. Initial prototype
3.3. Discussion
The testing for the HC-12, nRF24L01, and XBee module (three device sets) has been analysed in a
controlled environment at Taman Dahlia, Bukit Beruang, Melaka. This testing phase is performed to observe
the performance in terms of distance/range for potential collision use cases. The testing is directed with
having the three separate HC-12, nRF24L01 and XBee modules with various distances connected to a 9 V
battery placed in the range/distance discussed. These findings are presented in Tables 5-7.
Table 5. HC-12 range/distance
Range/distance
(m)
HC-12
Object
No-
object
5 ✓ ✓
10 ✓ ✓
20 ✓ ✓
40 ✓ ✓
60 ✓ ✓
80 ✓ ✓
100 ✓ ✓
120 ✓
✓Detected, Not detected
Table 6. nRF24L01 range/distance
Range/distance
(m)
nRF24L01
Object
No-
object
5 ✓ ✓
10 ✓ ✓
20 ✓ ✓
40 ✓ ✓
60 ✓
80 ✓
100 ✓
120
✓Detected, Not detected
Table 7. XBee range/distance
Range/distance
(m)
XBee
Object
No-
object
5 ✓ ✓
10 ✓ ✓
20 ✓ ✓
40 ✓ ✓
60 ✓ ✓
80 ✓ ✓
100 ✓ ✓
120 ✓ ✓
✓Detected, Not detected
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4. CONCLUSION
Vehicular communication is a promising field for the road transportation system. However, the
primary concern is addressing the communication medium between vehicles. In this paper, the project aims
to provide a conceptual communication medium between multiple nodes. Thus, several modules, namely
HC-12, nRF24L01, and Xbee, were used to analyse. The results acquired by observation, HC-12 and XBee
work on wider distances than nRF24L01. In the future, the research will be compared with ESP8266 and
LoRa and evaluate performance metrics, namely throughput, delay, jitter, and packet loss.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the use of service and facilities of the Connected Car Services
Research Group, Centre of Intelligent Cloud Computing at Multimedia University. The authors would like to
thank each individual who contributed directly or indirectly to this research. We thank the anonymous
reviewers for their constructive comments.
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BIOGRAPHIES OF AUTHORS
Sumendra Yogarayan is currently a Lecturer in the Faculty of Information
Science and Technology, Multimedia University (MMU), Melaka, Malaysia. He is an active
member of the Centre for Intelligent Cloud Computing (CICC), Multimedia University
(MMU). He graduated from Multimedia University (MMU) with a Master of Science
(Information Technology) in 2019 and a Bachelor of Information Technology (Security
Technology) in 2015. He is currently pursuing his Doctor of Philosophy (PhD) in Information
Technology at Multimedia University (MMU). His research interest includes intelligent
transportation systems, vehicular ad hoc networks, wireless communication, and mesh
networks. He can be contacted at email: sumendra@mmu.edu.my.
Siti Fatimah Abdul Razak has been a Lecturer at the Faculty of Information
Science and Technology, Multimedia University, since 2005. She graduated from Multimedia
University (MMU) with a Doctor of Philosophy (PhD) in Information Technology in 2018 and
a Master of Information Technology (Science and System Management) in 2004. She is also
an active member of the Centre for Intelligent Cloud Computing. Her research interest
includes vehicle safety applications, the internet of things, rule mining, information systems
development, and educational technology. She can be contacted at email:
fatimah.razak@mmu.edu.my.
8. Int J Inf & Commun Technol ISSN: 2252-8776
Comparative performance study of HC-12, nRF24L01, and XBee for vehicular … (Sumendra Yogarayan)
61
Mohd. Fikri Azli Abdullah has been a Lecturer in the Faculty of Information
Science and Technology at Multimedia University (MMU), Melaka, Malaysia, since 2005. He
graduated from the University of Melbourne, Australia, with a Master in Software System
Engineering. He was a researcher at Advance Network Lab at Chonnam National University,
South Korea, in 2010. His research interest includes mobile computing, image processing and
pattern recognition. He can be contacted at email: mfikriazli.abdullah@mmu.edu.my.
Afizan Azman is a Senior Lecturer at Taylors University, Selangor, Malaysia.
Previously he was the Vice Chancellor of Research and Innovation at Kolej Universiti Islam
Melaka (KUIM). He graduated from Loughborough University with a Doctor of Philosophy
(PhD) in Computer Science in 2013 and from University College of London with a Master of
Information Technology in Computer Science in 2005. His research interests include human-
computer interaction, artificial intelligence, vehicle systems and technology, data analytics,
and the internet of things. He can be contacted at email: afizan.azman@taylors.edu.my.
Vethanayagi Arultas received her Diploma in Information Technology in 2017
and Bachelor of Information Technology (Hons) Security Technology in 2022 from
Multimedia University (MMU). Her research interest includes wireless communication
technology, internet of things and sensor modules. She can be contacted at email:
vetha97@gmail.com.
Suneetha Sri Raman received her Bachelor of Information Technology (Hons)
Data Communications and Networking in 2020 from Multimedia University (MMU). Her
research interest includes internet of things, mobile and wireless network and embedded
device. She can be contacted at email: suneetha98@yahoo.com.