Academic literature on the topic 'Fast intervention vehicles'
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Journal articles on the topic "Fast intervention vehicles"
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Carvalho Barbosa, Rodrigo, Muhammad Shoaib Ayub, Renata Lopes Rosa, Demóstenes Zegarra Rodríguez, and Lunchakorn Wuttisittikulkij. "Lightweight PVIDNet: A Priority Vehicles Detection Network Model Based on Deep Learning for Intelligent Traffic Lights." Sensors 20, no. 21 (October 31, 2020): 6218. http://dx.doi.org/10.3390/s20216218.
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Minimizing human intervention in engines, such as traffic lights, through automatic applications and sensors has been the focus of many studies. Thus, Deep Learning (DL) algorithms have been studied for traffic signs and vehicle identification in an urban traffic context. However, there is a lack of priority vehicle classification algorithms with high accuracy, fast processing, and a lightweight solution. For filling those gaps, a vehicle detection system is proposed, which is integrated with an intelligent traffic light. Thus, this work proposes (1) a novel vehicle detection model named Priority Vehicle Image Detection Network (PVIDNet), based on YOLOV3, (2) a lightweight design strategy for the PVIDNet model using an activation function to decrease the execution time of the proposed model, (3) a traffic control algorithm based on the Brazilian Traffic Code, and (4) a database containing Brazilian vehicle images. The effectiveness of the proposed solutions were evaluated using the Simulation of Urban MObility (SUMO) tool. Results show that PVIDNet reached an accuracy higher than 0.95, and the waiting time of priority vehicles was reduced by up to 50%, demonstrating the effectiveness of the proposed solution.
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Shibl, Mostafa, Loay Ismail, and Ahmed Massoud. "Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers." Energies 13, no. 20 (October 17, 2020): 5429. http://dx.doi.org/10.3390/en13205429.
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Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the coordinated charging supports flattening the load profile. Therefore, an effective coordination technique is crucial for the protection of the distribution grid and its components. The substantial power used through charging EVs has undeniable negative impacts on the power grid. Additionally, with the increasing use of EVs, an effective solution for the coordination of EVs charging, particularly when considering the anticipated proliferation of EV fast chargers, is imminently required. In this paper, different machine learning (ML) approaches are compared for the coordination of EVs charging. The ML models can predict the power to be used in EVs charging stations (EVCS). Due to its ability to use historical data to learn and identify patterns for making future decisions with minimal user intervention, ML has been utilized. ML models used in this paper are (1) Decision Tree (DT), (2) Random Forest (RF), (3) Support Vector Machine (SVM), (4) Naïve Bayes (NB), (5) K-Nearest Neighbors (KNN), (6) Deep Neural Networks (DNN), and (7) Long Short-Term Memory (LSTM). These approaches are chosen as they are classifiers known to have the leading results for multiclass classification problems. The results found shed insight on the importance of the techniques used and their high potential in providing a reliable solution for the coordinated charging of EVs, thus improving the performance of the power grid, and reducing power losses and voltage fluctuations. The use of ML provides a less complex method to coordinate EVs, in comparison with conventional optimization techniques such as quadratic programming, and the use of ML is faster as it requires less computational power. LSTM provided the best results with an accuracy of 95% for predicting the most appropriate power rating (PR) for EVCS, followed by RF, DT, DNN, SVM, KNN, and NB. Additionally, LSTM was also the model with the smallest error rate, at a value of ±0.7%, followed by RF, DT, KNN, SVM, DNN, and NB. The results obtained from the LSTM model were similar to the results obtained from past literature using quadratic programming, with the increased speed and simplicity of ML.
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Cinat, Paolo, Salvatore Filippo Di Gennaro, Andrea Berton, and Alessandro Matese. "Comparison of Unsupervised Algorithms for Vineyard Canopy Segmentation from UAV Multispectral Images." Remote Sensing 11, no. 9 (April 30, 2019): 1023. http://dx.doi.org/10.3390/rs11091023.
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Technical resources are currently supporting and enhancing the ability of precision agriculture techniques in crop management. The accuracy of prescription maps is a key aspect to ensure a fast and targeted intervention. In this context, remote sensing acquisition by unmanned aerial vehicles (UAV) is one of the most advanced platforms to collect imagery of the field. Besides the imagery acquisition, canopy segmentation among soil, plants and shadows is another practical and technical aspect that must be fast and precise to ensure a targeted intervention. In this paper, algorithms to be applied to UAV imagery are proposed according to the sensor used that could either be visible spectral or multispectral. These algorithms, called HSV-based (Hue, Saturation, Value), DEM (Digital Elevation Model) and K-means, are unsupervised, i.e., they perform canopy segmentation without human support. They were tested and compared in three different scenarios obtained from two vineyards over two years, 2017 and 2018 for RGB (Red-Green-Blue) and NRG (Near Infrared-Red-Green) imagery. Particular attention is given to the unsupervised ability of these algorithms to identify vines in these different acquisition conditions. This ability is quantified by the introduction of over- and under- estimation indexes, which are the algorithm’s ability to over-estimate or under-estimate vine canopies. For RGB imagery, the HSV-based algorithms consistently over-estimate vines, and never under-estimate them. The k-means and DEM method have a similar trend of under-estimation. While for NRG imagery, the HSV is the more stable algorithm and the DEM model slightly over-estimates the vines. HSV-based algorithms and the DEM algorithm have comparable computation time. The k-means algorithm increases computational demand as the quality of the DEM decreases. The algorithms developed can isolate canopy vegetation data, which is useful information about the current vineyard state, and can be used as a tool to be efficiently applied in the crop management procedure within precision viticulture applications.
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Allotta, Benedetto, Lorenzo Brandani, Nicola Casagli, Riccardo Costanzi, Francesco Mugnai, Niccolò Monni, Marco Natalini, and Alessandro Ridolfi. "Development of Nemo remotely operated underwater vehicle for the inspection of the Costa Concordia wreck." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 231, no. 1 (August 3, 2016): 3–18. http://dx.doi.org/10.1177/1475090215605133.
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Remotely operated underwater vehicles are mobile robots increasingly used in underwater applications; these devices are widely used and suitable for different scenarios, for example, for patrolling and monitoring and also for underwater interventions. In the last 30 years, the remotely operated underwater vehicles have become more and more advanced; at the same rate with the progressive technological development of these vehicles, the market of the specialized component industry is fast-increasing. Generally speaking, a remotely operated underwater vehicle allows to investigate areas inaccessible or too dangerous for human beings. The use of remotely operated underwater vehicles during a mission, with the related implication of support ships and specialized pilots, or the involvement of professional divers, is usually associated with high costs. The reduction of these costs is an important topic in the underwater robotic field and the easy piloting of these mobile robots is a crucial aspect in their development. This article describes Nemo remotely operated underwater vehicle, a remotely operated underwater vehicle prototype specifically designed for the exploration of the Costa Concordia wreck, Isola del Giglio, Italy. Nemo remotely operated underwater vehicle can be considered a mini-remotely operated underwater vehicle, that is, a remotely operated underwater vehicle with weight less than 25 kg and easily deployable from a small boat. This article describes the main characteristics of the vehicle: the onboard control logic and on the development of a user-friendly graphical user interface for underwater navigation able to take advantage of its high maneuverability. It is worth to note that the developed graphical user interface enables to operate the vehicle even to inexperienced pilots. Preliminary experimental data collected during navigation are provided.
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Grigore, Lucian Stefanita, Iustin Priescu, Daniela Joita, and Ionica Oncioiu. "The Integration of Collaborative Robot Systems and Their Environmental Impacts." Processes 8, no. 4 (April 23, 2020): 494. http://dx.doi.org/10.3390/pr8040494.
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Today, industrial robots are used in dangerous environments in all sectors, including the sustainable energy sector. Sensors and processors collect and transmit information and data from users as a result of the application of robot control systems and sensory feedback. This paper proposes that the estimation of a collaborative robot system’s performance can be achieved by evaluating the mobility of robots. Scenarios have been determined in which an autonomous system has been used for intervention in crisis situations due to fire. The experimental model consists of three autonomous vehicles, two of which are ground vehicles and the other is an aerial vehicle. The conclusion of the research described in this paper highlights the fact that the integration of robotic systems made up of autonomous vehicles working in unstructured environments is difficult and at present there is no unitary analytical model.
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Kumar, Dr A. Dinesh. "Underwater Gripper using Distributed Network and Adaptive Control." Journal of Electrical Engineering and Automation 2, no. 1 (March 25, 2020): 43–49. http://dx.doi.org/10.36548/jeea.2020.1.005.
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Underwater identification and grasping of objects is a major challenge faced by the marine engineers even today. Nowadays, almost all underwater operations are either autonomous or tele-operated. In fact remotely operated vehicles (ROVs) are used to deal with inspection tasks and industrial maintenance whenever there is need for intervention. However, the field of autonomous underwater vehicle (AUV) is a blooming filed with research involving proper moving base control and forces interacting which leads to complicated configuration. Hence the presented work is focused implementation of end-effector with appropriate control and signal processing resulting in autonomous manipulation of movement under water.
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Cagliano, Anna Corinna, Antonio Carlin, Giulio Mangano, and Carlo Rafele. "Analyzing the diffusion of eco-friendly vans for urban freight distribution." International Journal of Logistics Management 28, no. 4 (November 13, 2017): 1218–42. http://dx.doi.org/10.1108/ijlm-05-2016-0123.
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Purpose The purpose of this paper is to investigate the diffusion dynamics of electric and hybrid commercial vans and its enabling factors in the city logistics (CL) contexts. The case of parcel delivery in Torino, Italy, is considered. Attention is paid to the influence on the choice of low impact vehicles of not only public strategies but also operational aspects characterizing urban freight distribution systems. Design/methodology/approach A System Dynamics model based on the Bass diffusion theory computes the number of adopters of low-emission vehicles together with the quantity of vans required and the associated economic savings. The model includes variables about freight demand, delivery frequency, van carrying capacity, routes, stops, distances traveled, and vehicle charging stations. A sensitivity analysis has been completed to identify the main diffusion levers. The focus is on advertising and other drivers, such as public contributions, taxes traditional polluting vehicles are subjected to, as well as on routing optimization strategies. Findings Advertising programs, green image, and word-of-mouth drive market saturation, although in a long time period. In fact, low-impact vehicles do not offer any economic advantage over traditional ones requiring higher investment and operating costs. Public incentives to purchase both green vehicles and charging stations, together with carbon taxes and a congestion charge affecting polluting vehicles, are able to shorten the adoption time. In particular, public intervention reveals to be effective only when it unfolds through a number of measures that both facilitate the use of environmentally friendly vehicles and discourage the adoption of traditional commercial vans. Route optimization also hastens the complete market saturation. Research limitations/implications This work fosters research about the mutual relationships between the diffusion of low-emission commercial vehicles and the operational and contextual CL factors. It provides a structured approach for investigating the feasibility of innovative good vehicles that might be part of assessments of CL measures and requirements. Finally, the model supports studies about the cooperation among stakeholders to identify effective commercial vehicle fleets. Practical implications This study fosters collaboration among CL players by providing a roadmap to identify the key factors for the diffusion of environmentally friendly freight vehicles. It also enables freight carriers to assess the operational and economic feasibility of adopting low-impact vehicles. Finally, it might assist public authorities in capturing the effects of new urban transportation policies prior to their implementation. Originality/value Most of the current CL literature defines policies and analyzes their effects. Also, there are several contributions on the diffusion of low emission cars. The present study is one of the first works on the diffusion of low-impact commercial vehicles in urban areas by considering the associated key operational factors. A further value is that the proposed model combines operational variables with economic and environmental issues.
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Sinha, Rajib, Lars E. Olsson, and Björn Frostell. "Sustainable Personal Transport Modes in a Life Cycle Perspective—Public or Private?" Sustainability 11, no. 24 (December 11, 2019): 7092. http://dx.doi.org/10.3390/su11247092.
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Life cycle-based studies endorse public transport to cause lower environmental pressures compared to a private car. However, a private car can cause lower environmental pressure when a public vehicle (bus or train) runs on a lower occupancy during an off-peak hour. This fact should be the basis for a more profound debate regarding public versus private transport. Many transport interventions are striving to reduce the number of car transports. To reach this goal, passengers need attractive alternatives to their reduced number of car travels (i.e., attractive public transport). This study aimed to develop a model allowing us to estimate potential environmental gains by changing travel behavior. A passenger travel model was developed based on life cycle inventories (LCI) of different travel modes to calculate environmental footprints. The model was applied in an intervention of public transport through temporary free public transport. The intervention was successful in significantly reducing the number of car transports (12%). However, total passenger kilometer travelled (PKT) increased substantially more, mainly by bus, but also train, bicycle and walking. The total energy, carbon and nitrogen oxide footprints were slightly increased after the intervention. If the commuters were assumed to travel during peak hours or the number of public transports were not affected by the increased number of commuters, the overall environmental footprints decreased. Our conclusions are that transport interventions are very complex. They may result in desired changes, but also in altered travel behavior, increasing overall impact. Thus, a very broad evaluation of all transport modes as well as potential positive social influences of the transport intervention will be necessary.
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Branner, Justin, and Ryan Custer. "Remotely operated vehicle (ROV) intervention technology allows early production from subsea wells." APPEA Journal 54, no. 2 (2014): 525. http://dx.doi.org/10.1071/aj13098.
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Subsea fields, particularly in deepwater, continue to challenge the economics of development for operators. Production of subsea wells by tying into existing facilities and rig-less intervention solutions undertaken during the initial phases of the project are being used to drive better economic outcomes. A recent deepwater development in the Asia Pacific region used locally developed technology to bring subsea wells into production using an ROV with a custom pumping package to open the formation isolation valve (FIV). This operation on the first two wells was done in 2012 from a vessel and the remaining wells were brought online using the same technology during 2013. As the operator wanted to tie-in production from existing subsea wells to an FPSO in an adjacent field while the development specific facility was still being constructed, an ROV-based remote intervention skid was developed to open the FIV and also leave a negative pressure above the surface-controlled subsurface safety valve (SCSSV). The skid was interfaced with a multi-quick-connect plate to provide bi-directional pumping capability to cycle the ratcheting mechanism of the FIV. This methodology allowed the operation to be completed much faster and at a lower cost compared with the use of a rig and is highly beneficial in locations where subsea wells have been drilled and need to be fast tracked for production. The project was a significant success for the operator and has proven to be a breakthrough in remote intervention technology and custom tooling capabilities in the Asia Pacific region.
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Lorenz, N., A. Nougtara, and P. Garner. "Episiotomy in Burkina Faso." Tropical Doctor 28, no. 2 (April 1998): 83–85. http://dx.doi.org/10.1177/004947559802800209.
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Episiotomy is a common obstetric intervention in many countries of the world, although little is known about rates in African countries. In recent years, the effectiveness of routine episiotomy to prevent severe tears and neonatal asphyxia has been questioned, and evidence shows that the procedure results in considerable maternal morbidity. This study estimates episiotomy rates in Burkina Faso. A high proportion of primigravidae (46%) received an episiotomy when trained midwives attended the delivery; a level which indicates the procedure has to be regarded as routine practice. The episiotomy rate was lower (26%) in primigravidae delivered by auxiliary midwives. This proportion is closer to recommended selective approaches derived from good research summaries. The tear rate in women assisted by midwife and auxiliary staff was similar, suggesting that women tear even when the procedure is performed. These results indicate that obstetricians and midwives in Burkina Faso should critically appraise whether routine episiotomy should be abandoned. The introduction of a labour chart is a good vehicle to introduce a policy on avoiding episiotomies.
Dissertations / Theses on the topic "Fast intervention vehicles"
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Fiala, Jiří. "Vyhodnocení efektivity zásahů složek Integrovaného záchranného systému Jihomoravského kraje u dopravních nehod." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-233058.
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The aim of this thesis is to evaluate the efficiency interventions in traffic accidents of the integrated rescue system. The thesis contains the evaluation if changing the system can improve the effectiveness of operations leading to save lives, health, property and the environment or minimize adverse impacts which are caused by an accident. The evaluation of the capability of recording devices to clarify the causes of traffic accident and their applications in the forensic engineering are also described.
Book chapters on the topic "Fast intervention vehicles"
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Poorsartep, Mohammad. "Self-Driving Cars." In Transcultural Marketing for Incremental and Radical Innovation, 96–105. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4749-7.ch005.
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The United Kingdom passed a series of acts to control the use of mechanically propelled vehicles on public highways. The Locomotive Act 1865 (Red Flag Act) limited the speed of self-propelled vehicles to six (6) km/hr in the country and three (3) km/hr in towns while requiring a crew of three. Since then, much progress has been made to adopt these mechanically propelled vehicles and build our lives and societies around them. Personal vehicles have become the dominant mode for transportation in many developed and developing countries. However, this fact begs the question of what the next evolution for the transportation industry is, and the answer is currently before us. Some may refer to it as self-driving, automated, autonomous, or even driverless cars that are capable of driving themselves from point A to point B with minimal or no human intervention. While admittedly the technology is not currently advanced adequately to safely and reliably accomplish the aforementioned task, this chapter aims to provide context and familiarize the reader with some of the necessary background information and then examine the challenges and possibilities that will be provided by this technology in a not so distant future.
Conference papers on the topic "Fast intervention vehicles"
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Al-Qeraiwi, Maha, Manar Al-Rashid, Nasser Rizk, Abdelrahman El Gamal, and Amena Fadl. "Hepatic Gene Expression Profile of Lipid Metabolism of Obese Mice after treatment with Anti-obesity Drug." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0214.
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Obesity is a global disorder with multifactorial causes. The liver plays a vital role in fat metabolism. Disorder of hepatic fat metabolism is associated with obesity and causes fatty liver. High fat diet intake (HFD) to mice causes the development of dietinduced obesity (DIO). The study aimed to detect the effects of anti-obesity drugs (sulforaphane; SFN and leptin) on hepatic gene expression of fat metabolism in mice that were fed HFD during an early time of DIO. Twenty wild types (WT) CD1 male mice aged ten weeks were fed a high fat diet. The mice were treated with vehicle; Veh (control group), and SFN, then each group is treated with leptin or saline. Four groups of treatment were: control group (vehicle + saline), Group 2 (vehicle + leptin), group 3 (SFN + saline), and group 4 (SFN + leptin). Body weight and food intake were monitored during the treatment period. Following the treatments of leptin 24 hour, fasting blood samples and liver tissue was collected, and Total RNA was extracted then used to assess the gene expression of 84 genes involved in hepatic fat metabolism using RT-PCR profiler array technique. Leptin treatment upregulated fatty acid betaoxidation (Acsbg2, Acsm4) and fatty acyl-CoA biosynthesis (Acot6, Acsl6), and downregulated is fatty acid transport (Slc27a2). SFN upregulated acylCoA hydrolase (Acot3) and long chain fatty acid activation for lipids synthesis and beta oxidation (Acsl1). Leptin + SFN upregulated fatty acid beta oxidation (Acad11, Acam) and acyl-CoA hydrolase (Acot3, Acot7), and downregulated fatty acid elongation (Acot2). As a result, treatment of both SFN and leptin has more profound effects on ameliorating pathways involved in hepatic lipogenesis and TG accumulation and lipid profile of TG and TC than other types of intervention. We conclude that early intervention of obesity pa could ameliorate the metabolic changes of fat metabolism in liver as observed in WT mice on HFD in response to anti-obesity treatment.
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Thorbole, Chandrashekhar K., Mary Aitken, James Graham, Beverly Miller, and Samantha Hope Mullins. "Assessment of the Dynamic Behavior of a Single Person ATV in Presence of a Passenger: Outcome on the Rider and Passenger Crash Impact Kinematics Using Computational Model." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-86164.
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An ATV (All-terrain vehicle) is a gasoline powered, fast moving off road vehicle often used for farming and industrial activities as well as recreational activities. The popularity of this type of vehicle has increased over the last decade with more than 10 million in use today. Most ATVs are designed for only single rider even though the seat of the ATV may appear big enough to carry a passenger. The presence of an additional person on a single person ATV greatly affects its dynamic handling characteristics. This change increases the risk of a crash and subsequent injuries to both riders. ATV crashes involving climbing and descending on steep hills are common. Lateral rollover crashes are often the result of riding an ATV at a high speed on uneven terrain. The presence of passenger on a single person ATV during these conditions changes the rider impact kinematics and resulting injury outcome, as the ATV behaves differently in the presence of an additional person. The computational model of a single person, adult-sized ATV, as developed previously for the study of child injury prevention, was used for this study. The multi-body computational model of this ATV was developed using biodynamic code MADYMO. This computational model was validated against the laboratory test for its dynamic and suspension characteristics. The tilt table test and the drop test were employed to compare the computational model result. This computer model was used to simulate the crash mechanism involving climbing and descending steep hills with two people on the ATV. This model was also used to simulate the lateral rollover of ATV with two people. The rider and the additional passenger on this single rider ATV were modeled using a 50th percentile male and a 5th percentile female. The two rider simulation was compared with single rider simulation for similar terrain and ATV speed to gain insight about the influence of this additional passenger weight on the crash kinematics of the ATV and the rider. These simulations will also be used in the future to generate more visually dramatic videos for educational intervention for ATV safety programs and other injury prevention activities.