Showing papers on "Dashboard published in 2019"

On combining Big Data and machine learning to support eco-driving behaviours

Abstract: A conscious use of the battery is one of the key elements to consider while driving an electric vehicle. Hence, supporting the drivers, with information about it, can be strategic in letting them drive in a better way, with the purpose of optimizing the energy consumption. In the context of electric vehicles, equipped with regenerative brakes, the driver’s braking style can make a significant difference. In this paper, we propose an approach which is based on the combination of big data and machine learning techniques, with the aim of enhancing the driver’s braking style through visual elements (displayed in the vehicle dashboard, as a Human–Machine Interface), actuating eco-driving behaviours. We have designed and developed a system prototype, by exploiting big data coming from an electric vehicle and a machine learning algorithm. Then, we have conducted a set of tests, with simulated and real data, and here we discuss the results we have obtained that can open interesting discussions about the use of big data, together with machine learning, so as to improve drivers’ awareness of eco-behaviours.

Image recognition system for rental vehicle damage detection and management

Abstract: Techniques are disclosed for rental vehicle damage detection and automatic rental vehicle management. In one embodiment, a rental vehicle management application receives video and/or images of a rental vehicle's exterior and dashboard and processes the video and/or images to determine damage to the vehicle as well as the vehicle's mileage and fuel level. A machine learning model may be trained using image sets, extracted from larger images of vehicles, that depict distinct types of damage to vehicles, as well as image sets depicting undamaged vehicles, and the management application may apply such a machine learning model to identify and classify vehicle damage. The management application further determines sizes of vehicle damage by converting the damage sizes in pixels to real-world units, and the management application then generates a report and receipt indicating the damage to the vehicle if any, mileage, fuel level, and associated costs.

PPTAM: Production and Performance Testing Based Application Monitoring

Abstract: It is mandatory to continuously assess software systems during development and operation, e.g., through testing and monitoring, to make sure that they meet their required level of performance. In our previous work, we have developed an approach to assess the degree to which configurations of a software system meet performance criteria based on a domain metric that is obtained by considering operational profiles and results from load test experiments. This paper presents our PPTAM tooling infrastructure that automates our approach and provides a dashboard visualization of the results.

An IoT System Design with Real-Time Stream Processing and Data Flow Integration

Abstract: This work presents an Internet of Thing (IoT) system design method with real-time processing that integrates various tools together as a model for further development or implementation of IoT system for various applications. The system has a data flow design on Apache NiFi for data stream processing that works with Apache Kafka for stream distribution, and data are stored in MongoDB. It also has data processing with Apache Storm that can process data quickly and display data on the Dashboard via Node-RED. In addition to the basic data storage system, there is also an additional function that can retrieve the stored data on database for further use by using REST API working on Node.js by Swagger standard. This foundation system is designed to be a prototype for those who want to design and use the platform with real-time processing characteristics. After testing, the designed system shows good working performance. It can display all values on the Dashboard completely in real-time and have a fast operation. The tools used in the study can be further developed for a more complex and larger system.

An Automotive Needle Meter Dynamic Test Method Based on Computer Vision and HILTechnology

Abstract: In the production of automotive gauge, one of the most important step is to test the meters on the dashboard some of which are needle meters. Based on computer vision technology, a dynamic automatic reading value test method is presented in the paper. With a hardware in the loop (HIL) platform simulating the actual vehicle running state and providing sensor signals or data via CAN(controller area network) bus for the tested automotive dashboard, the needle meters of the dashboard are tested by comparing the input and indication which is obtained through image process method. As the core technology of the method, how to read the indication of the needle meters automatically is expounded in detail. The proposed method is tested on an experimental system which is composed of a HIL platform based on VECTOR dSpace and a computer vision equipment including several MV-VS078FC cameras. The HIL and vision parts can coordinately work to fulfil the automatic test procedure. The meters can be dynamically driven and precisely automaticly read out.

Design of Digital CAN Based Car Dashboard Unit

Abstract: The paper describes the design and implementation of the CAN based digital dashboard unit used in the design study SCE of the electric car. The system consists of a CAN communication interface unit based on a PIC microcontroller and graphic programmable LCD displays. The work is not only described in terms of technical solution, but also in terms of design.

Research on Form Design of Automotive Dashboard Based on Kansei Engineering

Abstract: Understanding the driver's emotional needs for the dashboard is crucial to the success of vehicle design. In order to reduce the psychological burden of drivers in obtaining on-board information, the image of automobile dashboard was visually described and quantitatively analyzed with applying Kansei Engineering theory and the principle of Quantitative Class I. The predictive model between the adjectives of vehicle dashboard shape and perceptual image was established by using multiple linear regression analysis method, and the relationship between perceptual image and design elements was analyzed. The results show that the main sensory factors of shape design should be gentle and comfortable in the process of automobile dashboard design. To improve the fit between automobile dashboard design and driver's perceptual needs by transforming driver's emotional perception into design elements.

Proposed Design and Modeling of Smart Energy Dashboard System by Implementing IoT (Internet of Things) Based on Mobile Devices

Abstract: Electricity is one of the most important needs of the community, efficient use of electricity is very difficult to do when people lack awareness and discipline in using electricity, one of the problems that often occurs is when the homeowner is not at the location and wants it. to control electrical equipment. Internet of Things (IoT) is a concept with the aim of expanding the connectivity of internet networks connected to global networks, IoT can be used to control electronic equipment remotely or automatically. This study aims to build a remote control device that utilizes internet technology by carrying out the process of controlling existing devices on the internet network through systems on mobile devices, the contribution of this research is to create designs and models that will be used to build smart energy devices that are applied to home features smart by using sensor devices so that electronic equipment can be controlled according to the desired conditions, automatically or remotely on the android application. The smart energy dashboard is designed using the ESP8266 MCU node which is connected to the Firebase cloud which will move the digital signal to the relay as an electrical circuit breaker. Based on the results of system testing at 90.3% usability, 85.8% functionality and 90% Reliability, the Efficiency aspect test obtained the highest level of CPU efficiency at the level of 28% and dropped stably at a percentage of 10%, for the highest memory usage of 119.2MB begins with a memory usage of 47.7MB out of a total allocation of 143.1 MB. The conclusion of this study is that the IoT-based smart energy Dashboard proposal can help in controlling electrical devices in real time.

Internet of Thing (IoT) Based Remote Labs in Engineering

Abstract: This paper presents the development of a laboratory system at the Electrical Engineering Department of Zarqa University based on IoT and mobile application technologies to remotely run, implement and monitor the experiments that are required in the course of work by the student. Throughout a custom designed dashboard on the mobile application, the system, allows the students to extract results on a real time basis and submit their reports once they finish the experiments. The system comprises all the necessary devices, such as sensors, controlling and interfacing kits, cameras and others. Initially, the work is implemented on a Separately Excited DC (SEDC) motor experiment as one of the examples related to Electrical Machines Laboratory (EML) course as part of the courses delivered to the Electrical Engineering Program at Zarqa University. The proposed work mainly intents to provide an off-campus easy accessibility to the assigned experiment through a user-friendly interactive dashboard. For example in this experiment, the student can switch the direction of rotation of the motor and can run the motor at preset conditions with the capability to measure the electrical quantities such as voltage, current and power as well as other required parameters, such as speed and torque. The preliminary results demonstrated a proof of concept for remotely running such experiments via mobile applications, thereby allowing the students to perform their experiments in a fixable yet reliable manner. The work is still in progress and it is anticipated to expand the system to cover other experiments once the work is finalized.

Real-Time Traffic Monitoring System Using Spark

Abstract: Objective: Predict the total traffic count of streaming data in various routes to reduce traffic congestion and informing public about current traffic condition by displaying it in dashboard. Analysis: Real-time traffic monitoring can be made with the help of sensor connected devices, it generates huge volume and high speed data, Apache Kafka and Spark streaming engine is used for Processing these data. Findings: In existing system Traffic is predicted by deploying sensors in traffic signal lane and Apache hadoop used for processing data, it is batch processing system takes more time to process the data. In Proposed system total count of traffic predicted by using connected vehicles and Apache spark is used for processing live streaming data, by using spring boot total count of traffic is displayed in dashboard. Improvement: Real-time traffic prediction is done with live streaming data, Apache spark process data in-memory and dashboard updated for every five seconds

Data visualisation of vehicle crash using interactive map and data dashboard

Abstract: Vehicle crash contributes to a significant number of deaths and injuries in human races around the world. The government and the transportation expert work together around the clock to lessen the number of injuries and fatalities cause from vehicle crash issues. To come out with an effective solution whether from improving the trafficking system including road conditions or increasing awareness among drivers, the experts must analyse the data of vehicle crash from the past decades to find the major causes and come out with a decision. The lack of suitable techniques and tools to analyse a large amount of data is a deterrent in analysing vehicle crash datasets, and the process costs a lot of time. Data visualisation is a technique that allows people to display data in a more infographic form via data visualisation models. Therefore, this study aims to promote and elaborate more on data visualisation techniques using the interactive map and data dashboard to display vehicle crash data. Interactive map and data dashboard can help the government and transportation experts to describe vehicle crash data for them to make right decision to lessen car accident issues. The interactive map focuses on displaying vehicle crash data in map presentation while the data dashboard shows some charts and graph that describe the vehicle crash data in the statistical form. This study can be a reference model of creating interactive map and data dashboard or enhancing the capabilities in managing vehicle crash.

Comprehensive Digital Instrument Cluster for Vehicle Monitoring by Using Flutter Framework

Abstract: Engineers have considered many aspects on designing a car behavior before launching it, based on certain customer market. Different manufacture may have different concerns. Moreover, the longer being used, the performance may degrade as well. These two aspects are not visible to user except the one available on dashboard. Thus, judging car conditions is mostly done based on user feelings, which is subjective measurement and varies among human. For that purpose, this paper proposes vehicle monitoring system with quantitative measurement to provide consistent measurement. The measurement focuses on two observations; vehicle internal condition through OBD-II interface, and passenger comfort based on standalone sensors. The monitoring results can be used for prospective buyer and for performance monitoring from time to time. In order to provide a stylish look with comprehensive information, a comprehensive digital instrumentation cluster with flutter framework is proposed. Finally, the monitoring on real riding is provided and summarized at the end.

Implementation of Weigh-in-Motion Data Quality Control and Real-Time Dashboard Development

Abstract: Commercial motor vehicles travel an average of 294 million miles daily on Indiana’s roads. State agencies have implemented weigh-in-motion (WIM) sensors to weigh, count, and classify commercial vehicles at high­ way speeds. Recent advancements in communications, computational capacity, and memory storage have en­ abled real-time recording and permanent storage of data from every WIM station statewide. Improperly load­ ed commercial vehicles cause exponentially greater damage to roadways. In the year 2016 alone, INDOT’s WIM stations produced approximately 550 million total vehicle records per year. This study had two objectives:

SmartDashCam: automatic live calibration for DashCams

Abstract: Dashboard camera installations are becoming increasingly common due to various Advanced Driver Assistance Systems (ADAS) based services provided by them. Though deployed primarily for crash recordings, calibrating these cameras can allow them to measure real-world distances, which can enable a broad spectrum of ADAS applications such as lane-detection, safe driving distance estimation, collision prediction, and collision prevention Today, dashboard camera calibration is a tedious manual process that requires a trained professional who needs to use a known pattern (e.g., chessboard-like) at a calibrated distance. In this paper, we propose SmartDash-Cam, a system for automatic and live calibration of dashboard cameras which always ensures highly accurate calibration values. Smart-DashCam leverages collecting images of a large number of vehicles appearing in front of the camera and using their coarse geometric shapes to derive the calibration parameters. In sharp contrast to the manual process we are proposing the use of a large amount of data and machine learning techniques to arrive at calibration accuracies that are comparable to the manual process. SmartDashCam implemented using commodity dashboard cameras estimates realworld distances with mean errors of 5.7 % which closely rivals the 4.1% mean error obtained from traditional manual calibration using known patterns.

Vehicle heads-up display

Abstract: A display system for a vehicle. The display system includes a display engine that displays an image visible to a driver of the vehicle. In a first configuration, the display engine projects vehicle operating information directly in front of the driver. In a second configuration, the display engine projects an augmented reality image of an environment ahead of the vehicle directly in front of the driver. In a third configuration, the display engine projects entertainment images at a center of a dashboard of the vehicle between a driver's seat and a front passenger seat.

Development of Alphanumeric Digital Fuel Gauge for Automotive Applications

Abstract: The objective of this paper is to describe drawbacks in traditional fuel gauges and solution for those drawbacks. In traditional fuel gauges, fuel reading is displayed in between E to F (Empty to full) on a dashboard. Same way in digital fuel gauges the fuel is shown in bars between E to F. In both cases fuel readings are displayed in rough indication format and not in liters. This is a major drawback in both the cases and this drawback causes disruption to a driver or rider over the fuel quantity. This major issue can be overcome by using a transducer that measures fuel in milliliters. This paper discusses how this transducer is used for measuring fuel in liters, calculating mileage for every liter of fuel, reducing shaking error, display

Concept simulator K3F: a flexible framework for driving simulations

Abstract: Developing and evaluating automotive user interfaces and driver assistance systems in real vehicles and in simulators is an effortful and costly process. To reduce the effort in defining and conducting user studies, this demo introduces the concept simulator K3F. K3F is a highly flexible driving simulation environment that allows a quick and easy modification and exchange of its hard- and software components including simulation software, dashboard/infotainment, and peripheral systems. The K3F software supports a convenient setup of user studies and a comprehensive collection of data. It simplifies the creation and modification of virtual environments and the development of real-world street scenarios. The integration of a driver model based on the ACT-R cognitive architecture allows not only the explanation of observed behavior, but also the prediction of human driving patterns.

Occupant protection system

Abstract: In severe traffic accidents, crumpling the front of the car causes the passenger's leg get stuck between the seat and the car's dashboard. In this article, the condition of the seat and occupant safety sack is checked, which keeps the passenger in place, in heavy crashes, then raises the occupant's knee, and pulls the front seats back as far as possible.

Ergonomic design of electric vehicle instrument panel: a study case on Universitas Indonesia’s national electric car

Abstract: An electric car is an environmentally friendly car that becomes an alternative substitute for a conventional car. Similar to a conventional car, it is also completed with an indicator panel on its dashboard which is a display to present information to connect machine and human on a real time. However, there are some differences information required between electric car's indicator panel and the conventional car's indicator panel. This research is conducted to find the proper design and also to complete information requirements of indicator panel of an electric car, and the object of this research is The Universitas Indonesia's National Electric Car. This research conducted based on two major aspects, that is consumer's preferences, using conjoint analysis to obtain top three design, and also ergonomic, by testing three combinations of indicator panel design which produced by conjoint analysis using eye tracking method, in order to enhance the value of indicator panel for Universitas Indonesia's National Electric Car and also to meet consumer's preferences and needs. This research found the best design combination that has the least number of fixations and saccades eye movement, also the least response time.

Evaluation of the Temperature Distribution and Structural Deformation of the Car Dashboard Subjected to Direct Sunlight

Abstract: A situation in which the car is directly parked under the sunlight needs to be considered as one of unavoidable operating conditions.The thermal phenomenon perceived by car dashboard might affect its functionality. The biomechanical function of the dashboard focused on the thermo-structural evaluation due to the direct sunlight was numerically simulated and investigated in this work. Polypropylene was chosen as the main dashboard material.The aims are to evaluate the temperature distribution, stress distribution and structural deformation of a car dashboard subjected to direct sunlight and due to the outside air goes inside the passenger compartment through an air duct.The material yieldsa small temperature gradient due to both direct sunlight and air flow through the air duct.By imposing 400 W/m2 heat flux on the dashboard surface, the stress distribution mainly occurs in the part of the applied constraints and the air duct placement, which has maximum value 19.56 MPa. The displacement of the dashboard is 0.0357 mm which is chiefly experienced by the front-centre part of the dashboard surface.

Decorative system for vehicle interiors

Abstract: The invention relates to a decorative system based on providing very thin flexible screens on the inner surface of the passenger compartment of a motor vehicle, e.g. on the dashboard, central column, doors, etc., which screens adapt to the appearance of the vehicle and are touch sensitive, said screens being connected to control software such that they can display different contents, e.g. images, information relating to the vehicle, or simply imitate different types of vehicle finishes or materials.

Display method of vehicle instrument panel, vehicle-mounted terminal and storage device

Abstract: The invention discloses a display method of a vehicle instrument panel, a vehicle-mounted terminal and a storage device. The method includes the following steps that 1, when a system is started, the basic information data of the engine speed, the vehicle speed and the fuel quantity of a current vehicle is obtained through detection; 2, the basic information data is transmitted to a display screenand displayed through a dashboard with an image; 3, instructions for switching to different function modes are received from the owner of a vehicle; 4, the function modes are switched, and corresponding parameter data is detected according to the switched function mode; 5, the corresponding parameter data is sent to a display screen for displaying with a corresponding image. Various vehicle parameters can be detected through a system, the basic information of the dashboard is displayed on the display screen, other vehicle information and multimedia information are displayed through switching,the function of a central control panel and the function of the dashboard are combined, the utilization ratio of a traditional dashboard is improved, the owner of the vehicle can know the basic information of driving in time, and the driving safety is ensured.

Vision-based mobile application for supporting the user in the vehicle operation

Abstract: In this paper the automatic vision-based mobile application for supporting the vehicle user is proposed. The system, using the image taken with the typical smartphone camera, recognizes three types of information located on the vehicle body: text data, displayed dashboard icons, and components in the engine compartment. The modern programming tools and recognition algorithms, including deep neural networks, were used in the implementation regarded to the limited efficiency of mobile devices. Preliminary tests using prepared database indicate on a high recognition performance. Recognition results and instructions are presented to the user in an accessible way using techniques of the augmented reality.

Smart Fleet Management System Using IoT, Computer Vision, Cloud Computing and Machine Learning Technologies

Abstract: The objective of this paper was to present the effective use of niche technologies in solving most critical problems of Fleet Industry. The proposed fleet management system described in the paper used a rich set of technologies like Internet of Things(IoT), Cloud Computing, Computer Vision, Machine Learning, Deep Learning and Embedded. IBM Watson IoT and Heroku platforms hosted the application to receive data from vehicle dashboard device. Driver’s face authentication and driving pattern monitoring, Fuel Consumption prediction modules used OpenCV (Computer Vision), SVN (Machine Learning) and CNN (Deep Learning) techniques. Vehicle’s Telematics, deviation from route, unauthorized entry in the container, continuous monitoring of trucks internal environment was handled by a high end embedded device with a set of sensor box, cameras, OBD-Π device and a gateway. Real data was collected to train and test the face detection and authentication models used in the system. Simulation results demonstrated that the proposed approach can achieve realistic demand of handing and manipulating humongous data coming every few seconds from several vehicles through IoT, NoSQL CloudantDB database and Cloud Computing. The paper also presented the architecture of the system and experimentation results done for various modules of the system.

A method of vehicle dashboard image location based on machine vision

Abstract: In order to solve the problem of the low efficiency and precision of manual eye inspection of vehicle dashboard, a method of dashboard image location based on machine vision is proposed. The relationship between spatial coordinates and pixel coordinates is established through nine-point calibration. In this coordinate system, PatQuick algorithm is used to roughly locate the dashboard. After that the image is marginalized by the Sobel Operator. Then the Blob algorithm is used to precisely locate the scale lines. At last, liquid crystal display character is located by combining PatMax algorithm and Blob algorithm. This method can locate the graph information accurately, reduce the deviation of dashboard display, improve automobile quality inspection rate and have important significance for the practical application of the image positioning of the automobile dashboard.

Multi-channel temperature measurement system with remote dashboard for electric vehicle

Abstract: A multi-channel temperature measurement system for an electric vehicle with a remote control dashboard capability is presented in the paper. The presented system is intended to be used for monitoring of batteries’ temperatures in hybrid or electric vehicles. Generally it is necessary in case of charging or discharging a battery stack consisting of several batteries which should be monitored independently to avoid any malfunctions or catastrophic results caused by overvoltage, under-voltage or excessive heating. The presented system incorporates multi-channel temperature measurements with digital temperature sensors, a FPGA device which collects data from sensors and translates it to CAN bus frames. CAN bus is incorporated for communication with a Battery Management System. To allow the remote monitoring, the system is equipped with a single board micro-computer running Node RED software. The structure of the system as well as particular devices are described in the paper.

CAN Bus Comunication using LabViewSystem

Abstract: The paper deals with the CAN bus communication between the infotainment elements and the drive component of the car using LabViewsystem. In the introduction, it is briefly described the communications bus used in automotive systems. These include buses CAN, LIN, MOST and Flexray. It is described their basic features, benefits and utilization. The main task is graphically program and builds a dashboard that will resemble a real dashboard from a Volkswagen Golf 5. Using the virtual dashboard built in LabView,it is controlled the real dashboard.

Adaptive backup structure for airbag support

Abstract: In a vehicle having a display mounted forward of a passenger seat on a dashboard and angled toward a driver seat adjacent the passenger seat, the display is moveable from the angled position to a position flush with the dashboard, and an airbag system is configured to deploy an airbag cushion that displaces the display from the angled position to the position flush with the dashboard to ensure that the airbag cushion has an adequate backup or support surface.

Distraction-Free Car Dashboard Control Through Gesture Recognition

Abstract: In this paper, a gesture recognition-based human–vehicle interaction system has been developed which primarily aims to reduce driver distraction while operating dashboard controls in an automobile. This is achieved through simple gestures and camera positioning which ensures the driver keeps his eyes on the road and hands on the wheel. This method is also compared with other types of inputs which aim to achieve better ergonomics. These inputs include voice commands, physical inputs like steering-mounted controls and also existing gesture recognition methods. This method overcomes the limitations of the aforementioned input techniques by providing a simpler and effective alternative. Said system is found to be superior compared to existing dashboard control media on grounds of operability, execution time and ease of operation.