articles by Rodolfo Meneguette
<p>Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamli... more <p>Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT. The main goal of the proposed solution is to reduce the average trip time, CO emissions and fuel consumption by allowing motorists to avoid congested roads. The simulation results show that our proposed solution leads to short delays and a low overhead. Moreover, it is efficient with regard to the coverage of the event and the distance to which the information can be propagated. The findings of the investigation show that the proposed solution leads to (i) high hit rate in the classification of the level of congestion, (ii) a reduction in average trip time, (iii) a reduction in fuel consumption, and (iv) reduced CO emissions</p>
Papers by Rodolfo Meneguette
IEEE Communications Magazine
Computer Networks, Aug 1, 2017
Intelligent Transportation Systems (ITS) aim to streamline the operation of vehicles and manage v... more Intelligent Transportation Systems (ITS) aim to streamline the operation of vehicles and manage vehicle traffic, while other information ITS can strengthen Cloud computing by storing and processing the collected information. Resource management is a particularly challenging issue for vehicular cloud development. In this paper, we propose a protocol to assist in the search and management of resources in a vehicular cloud without depending on the support of roadside infrastructure. Thus, vehicles are expected to organize themselves and establish collaborations to manage and share their resources. Simulation results show that, in comparison to other works, the proposed protocol achieved an increase in the average cluster head duration of around 18%, an increase of 13% of member vehicles, a decrease of 3% of cluster head changes, and a reduced amount of clusters by around 11%. The proposed protocol also achieved a higher availability of resources, by about 96%, and a lower time for search and allocation (around 0.5 (ms) to search 1 hop, and 1(ms) to search 3 or 2 hops).
IEEE Access, 2022
Data Dissemination protocols are used for several vehicular applications, varying from warning me... more Data Dissemination protocols are used for several vehicular applications, varying from warning messages to real-time video delivery. The majority of literature solutions consider the distance from the sender to choose the vehicle to forward the message. Basically, the solutions introduce a delay in the forwarding procedure, which is inversely proportional to the distance from the sender vehicle. In order to improve the forwarding procedure, this work introduces the concept of Road Covered Area to improve the overall data dissemination process and we describe how to calculate the road covered area by a node transmission. We present the D&RCA, the combination of Distance and Road Covered Area strategies to enhance the re-transmission during communication. Instead of considering the distance, we propose a function to combine the distance and road covered area to introduce a small delay before re-transmissions. We compare the proposed protocol with literature solutions considering the metrics of number of collisions, network coverage and communication latency for different density of vehicles in the network. When the network has 700 vehicles/km 2 , the data dissemination latency and number of collisions of the proposed D&RCA is, respectively, 1.24 and 1.32 times smaller than the literature solutions. When we increase the density of vehicles, all evaluated solutions present a network coverage above 90%.
GLOBECOM 2022 - 2022 IEEE Global Communications Conference, Dec 4, 2022
Research Square (Research Square), Aug 10, 2023
Wildlife roadkill is a recurring, dangerous problem that affects both humans and animals and has ... more Wildlife roadkill is a recurring, dangerous problem that affects both humans and animals and has received increasing attention from environmentalists worldwide. Addressing this problem is difficult due to the high investments required in road infrastructure to effectively reduce wildlife vehicle collisions. Despite recent applications of machine learning techniques in low-cost and economically viable detection systems, e.g., for alerting drivers about the presence of animals and collecting statistics on endangered animal species, the success and wide adoption of these systems depend heavily on the availability of data for system training. The lack of training data negatively impacts the feature extraction of machine learning models, which is crucial for successful animal detection and classification. In this paper, we evaluate the performance of several state-of-the-art object detection models on limited data for model training. The selected models are based on the YOLO architecture, which is well-suited for and commonly used in real-time object detection. These include the YoloV4, Scaled-YoloV4, YoloV5, YoloR, YoloX, and YoloV7 models. We focus on Brazilian endangered animal species and use the BRA-Dataset for model training. We also assess the effectiveness of data augmentation and transfer learning techniques in our evaluation. The models are compared using summary metrics such as precision, recall, mAP, and FPS and are qualitatively analyzed considering classic computer vision problems. The results show that the architecture with the best results against false negatives is Scaled-YoloV4, while the best FPS detection score is the nano version of YoloV5.
Ad hoc networks, Oct 1, 2023
Denial-of-Service (DoS) attacks have been extensively studied in the literature, especially in th... more Denial-of-Service (DoS) attacks have been extensively studied in the literature, especially in their most dangerous form, the Distributed Denial-of-Service (DDoS). Database, a critical infrastructure for services, has mechanisms for recording information (logs) of SQL queries and sessions. Although they are vulnerable to DDoS, they are not entirely covered by commercial tools or research on such a detection. Machine Learning (ML) techniques are highly effective in identifying patterns in data such as database SQL logs. Thus, this work proposes the application of ML to detect DDoS attacks on a database from the logs of queries executed on it. As a result, the classification obtained an F1score of 94.44%, which indicates the effectiveness of the proposed approach.
Journal of information security and applications, Jun 1, 2022
International journal of computer applications in technology, 2022
IEEE Latin America Transactions, Dec 1, 2017
Most of the applications for intelligent transport system are developed by an information center,... more Most of the applications for intelligent transport system are developed by an information center, which can be a data center or a cloud. For vehicles to have access to the services offered by these systems, the vehicles usually need to be connected to a roadside infrastructure that gives them access to the internet. To the efficient use of such services, a vehicle mobility management mechanism is required to allow a seamless data transfer without any interruption in connection. In addition, if there is any change of access point, this exchange occurs transparently to the user. In this paper, we propose a mobility management mechanism that will have to manage the data flow of more than one active interface simultaneously with the objective of maximizing the flow of information trafficked, reducing the time of the exchange of flow between the interfaces, consequently reducing the delay.
2022 17th Iberian Conference on Information Systems and Technologies (CISTI), Jun 22, 2022
2022 17th Iberian Conference on Information Systems and Technologies (CISTI), Jun 22, 2022
IEEE Latin America Transactions, Feb 1, 2022
The high growth of urban centers brings several problems for the population, such as socioeconomi... more The high growth of urban centers brings several problems for the population, such as socioeconomic and health problems due to toxins, polluting gases, delay in emergency care, and the stress to which citizens are exposed to traffic. Generally, for predicting the impact of a given action in the city, simulations are used to take into account the mobility of its inhabitants. These simulations must correspond with the environment that you want to be represented. Therefore, datasets with real data, make the simulations more reliable so that the results obtained are more satisfactory. The project aims to build a dataset with real data of user locations and traffic interventions for network simulations, optimize services for intelligent transport systems, and improve urban mobility in the city of Catanduva-SP. The results were performed on the mobile application (TIMELESS) and show that it consumes few smartphone resources (data, memory, and battery) to collect and generate the data set, compared to the use of other applications in the same segment (traffic monitoring and route suggestion).
Due to technological advances, millions of data are continuously generated during the journeys ma... more Due to technological advances, millions of data are continuously generated during the journeys made by people daily. This data can be essential to present decision making and thus contribute to minimizing the effects of traffic congestion on people’s lives. It is vital to store that data in an organized manner so that it is processed and used efficiently. In this project, we present TRUDE, a tool for generating a dataset with data collected during users’ urban mobility, and through notifications of interventions. The tool was developed in modules that collect data on two fronts: by a web application, where users manage the data entry related to the programmed interventions for the city of Catanduva/SP, and by a mobile app that collects the user’s routes during their journeys, through their mobile devices. The results presented demonstrate that the mobile application tool consumes little memory, battery, and data of the devices during its execution. Also, due the dataset is possible showing drivers the interventions that are generated on their routes, presenting in advance another alternative to improve the flow of vehicles in the city.
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articles by Rodolfo Meneguette
Papers by Rodolfo Meneguette