Vehicle Carbon Footprint Management and Analysis System

Abstract

The present invention relates to a method and system for precisely measuring and managing a vehicle's carbon footprint using a Geographic Information System (GIS). To this end, the present invention comprises a vehicle state detection unit for detecting vehicle state data; a route setting unit for setting a driving route; a carbon footprint generation unit for generating a carbon footprint based on the state data; and a database for storing the vehicle carbon footprint and the route carbon footprint. The above-described route setting unit provides a vehicle carbon footprint management and analysis system using a geographic information system, wherein the route setting unit performs the steps of: setting a minimum distance driving route; setting a plurality of nodes on the minimum distance driving route; detecting a route carbon footprint between the nodes from the database; searching for a route with a route carbon footprint smaller than the set value when the detected route carbon footprint is larger than the set value; and changing the driving route to the searched route. Accordingly, according to the present invention, by combining real-time location and operation data of a vehicle with a Geographic Information System (GIS), carbon emissions can be precisely monitored and vehicle operation strategies optimized, thereby enabling energy savings and carbon emission reduction.

Description

Technology Field

[0001] The present invention relates to a vehicle carbon footprint management and analysis system, and specifically to a method and system capable of precisely measuring and managing a vehicle's carbon footprint using a Geographic Information System (GIS). Background Technology

[0002] Globally, reducing carbon emissions is emerging as a critical task for environmental protection and sustainable development. In particular, vehicle operation in urban transportation is identified as one of the major causes of air pollution and greenhouse gas emissions. Accordingly, the accurate measurement and analysis of vehicle carbon emissions are essential for developing eco-friendly transportation systems.

[0003] To this end, a tool capable of accurately detecting the vehicle's condition is required. In particular, since the condition of an electric vehicle, including the battery, fluctuates significantly depending on driving conditions, assessing the vehicle's status based solely on mileage results in a large margin of error.

[0004] According to Registered Patent No. 10-1449917 based on prior art, there is a driving information collection unit that collects driving information including location information of the vehicle from a vehicle terminal installed in the vehicle via a wireless communication network and temporarily stores it; an emission information calculation unit that calculates emission information of air pollutants emitted during the operation of the vehicle using driving information of the vehicle received from the driving information collection unit and vehicle information stored in a vehicle registration database, and stores the calculated emission information in an emission database; and a driving analysis information generation unit that generates driving analysis information by analyzing driving information of the vehicle received from the driving information collection unit and vehicle information stored in the vehicle registration database, and stores the generated driving analysis information in a driving analysis information database. A carbon emission and operation information analysis system using real-time operation information of a vehicle is presented, characterized by including: an operation statistics information generation unit that generates operation statistics information including carbon emissions using vehicle information stored in the vehicle registration database, emission information stored in the emission information database, and operation analysis information stored in the operation analysis information database, and stores the generated operation statistics information in the operation statistics information database.

[0005] However, the aforementioned conventional technology has a problem in that it only calculates carbon emissions based on driving information and fails to provide the driver with information to minimize carbon emissions. The problem to be solved

[0006] The present invention aims to solve the aforementioned problems, specifically by combining real-time vehicle location and operation data with a Geographic Information System (GIS) to precisely monitor carbon emissions and optimize vehicle operation strategies, thereby promoting energy savings and carbon emission reduction.

[0007] In addition, it is intended to provide drivers with detailed information regarding their vehicle's carbon footprint, thereby offering information that enables them to save energy and drive efficiently.

[0008] Furthermore, it is intended to provide local governments and urban planners with high-resolution geographical information regarding carbon emissions and energy consumption patterns, thereby supporting sustainable decision-making in urban transportation planning and infrastructure development. means of solving the problem

[0009] To achieve the above objective, the present invention comprises a vehicle state detection unit for detecting vehicle state data; a path setting unit for setting a driving path; a carbon footprint generation unit for generating a carbon footprint based on the state data; and a database for storing vehicle carbon footprints and path carbon footprints.

[0010] The above-described route setting unit provides a vehicle carbon footprint management and analysis system using a geographic information system, wherein the route setting unit performs the steps of: setting a minimum distance driving route; setting a plurality of nodes on the minimum distance driving route; detecting a route carbon footprint between the nodes from the database; searching for a route with a route carbon footprint smaller than the set value when the detected route carbon footprint is larger than the set value; and changing the driving route to the searched route.

[0011] The above vehicle is an electric vehicle, and it is preferable that the carbon footprint generation unit generates a vehicle carbon footprint using battery consumption, charging data, and the carbon emission coefficient of the corresponding region received through the vehicle status detection unit.

[0012] It is preferable that the carbon footprint generation unit above generates a path carbon footprint by summing the carbon footprints of each vehicle generated between the nodes.

[0013] It is desirable that the vehicle carbon footprint management and analysis system further comprises a driving feedback provision unit, wherein the driving feedback provision unit detects optimal driving characteristic data that minimizes carbon emissions for each node, and compares the driving characteristic data from the vehicle state detection unit with the optimal driving characteristic data, and if the difference is greater than or equal to a set value, displays an alarm to the corresponding vehicle. Effects of the invention

[0014] According to the present invention, by combining real-time location and operation data of a vehicle with a Geographic Information System (GIS), carbon emissions can be precisely monitored and vehicle operation strategies optimized, thereby enabling energy savings and carbon emission reduction.

[0015] In addition, it can provide drivers with detailed information regarding the vehicle's carbon footprint, thereby offering information that enables them to save energy and drive efficiently.

[0016] Furthermore, by providing local governments and urban planners with high-resolution geographic information regarding carbon emissions and energy consumption patterns, it can support sustainable decision-making in urban transportation planning and infrastructure development. Brief explanation of the drawing

[0017] FIG. 1 is a configuration diagram showing the configuration of a vehicle carbon footprint management and analysis system according to the present invention; Figure 2 is an example diagram showing a screen displayed on a vehicle by the system of Figure 1. Specific details for implementing the invention

[0018] The configuration and operation of a specific embodiment according to the present invention will be described in detail with reference to the drawings.

[0019] The vehicle carbon footprint management and analysis system according to the present invention may be installed on a central server and comprises a vehicle status detection unit (200), a route setting unit (300), a carbon footprint generation unit (400), a driving feedback provision unit (500), a carbon emission right request unit (600), a traffic flow analysis unit (700), a climate analysis unit (750), a wireless communication unit (800), and an artificial intelligence learning unit (900).

[0020] The vehicle state detection unit (200) receives state information generated during the vehicle's operation in real time using various sensors such as a speedometer and a fuel consumption sensor, or equipment such as an OBD2 module. For example, the vehicle state detection unit can receive battery state information transmitted from an electric vehicle BMS (Battery Management System) to receive state data such as the battery's voltage, current, temperature, SOC, and SOH, and can receive state data such as the vehicle's latitude, longitude, and altitude using GPS or GIS. In addition, it receives state data regarding the motor's RPM, accelerator and brake operation time, etc., in real time and stores it in a storage unit.

[0021] The above status data is processed by the vehicle's onboard computer and transmitted to the vehicle status detection unit via a wireless communication module in a standardized format. This transmission process maintains data security through encryption, and the data is stored in an internal storage unit to prepare for cases where the network connection is unstable.

[0022] Various types of data, including collected status data, are stored on a central server, which processes the collected data using a big data processing platform. This platform may include Hadoop, Spark, or similar distributed computing systems and is capable of rapidly processing large volumes of data. The data first undergoes a preprocessing stage to remove noise and normalize the data. Subsequently, parts requiring complex calculations, such as carbon emission calculations, are processed using cloud-based computing resources.

[0023] The above-mentioned route setting unit (300) determines the route for a vehicle to travel based on a starting point and an ending point on a map by referring to a Geographic Information System (GIS), and the route can be set based on criteria such as minimum time and minimum distance. In addition, the above-mentioned route setting unit can calculate and display the estimated battery consumption and driving range for the set route, and can calculate the estimated battery consumption for multiple routes and display the route predicted to have the lowest battery consumption among them on the vehicle's display unit.

[0024] The carbon footprint generation unit (400) above generates a carbon footprint based on the vehicle's status data and stores it in a database. The carbon footprint is data that estimates the amount of carbon emitted according to location, and the carbon footprint is further divided into a vehicle carbon footprint and a route carbon footprint and calculated separately.

[0025] The above vehicle carbon footprint is calculated as the total sum of carbon emissions emitted by each vehicle, and the route setting unit sets multiple nodes according to the vehicle's driving route, and the above vehicle carbon footprint can be calculated as the total sum of carbon emissions emitted between each node.

[0026] In this case, for internal combustion engine vehicles, CO2 emissions are estimated by applying emission factors provided by environmental protection agencies based on vehicle fuel consumption and engine characteristic data, while for electric vehicles, indirect emissions can be calculated using battery consumption and charging data, as well as the carbon emission factors of the local electricity.

[0027] Using the above vehicle carbon footprint, it is possible to calculate carbon emissions for each vehicle by time of day, such as monthly or weekly, or to calculate the accumulated carbon emissions of a specific vehicle along a specific route.

[0028] The above path carbon footprint refers to the total sum of carbon emissions from vehicles as they move along a vehicle's driving path, and the path carbon footprint can be calculated as the total sum of carbon emissions from vehicles between each node over time.

[0029] The carbon footprint generation unit (400) integrates data collected from GPS and various sensors mounted on the vehicle with a geographic information system to analyze the location, driving speed, driving pattern, etc. of each vehicle. In addition, it can evaluate environmental factors affecting the energy efficiency and carbon emissions of the vehicle, including real-time weather data and road conditions. The driving pattern may include dynamic variables such as the vehicle's acceleration, braking pattern, and battery status.

[0030] That is, the traffic flow analysis unit (700) analyzes traffic flow data such as traffic volume on the driving route and the average speed of vehicles, and transmits this to the carbon footprint generation unit (400). In addition, the climate analysis unit (750) collects climate data regarding weather such as precipitation, rainfall, temperature, and humidity, and transmits this to the carbon footprint generation unit (400).

[0031] The artificial intelligence learning unit (900) of the system can perform artificial intelligence learning using the above traffic flow data, climate data, and road slope data from a geographic information system as input data, and the energy consumption or carbon emission amount as a label, and accordingly, generate a first carbon emission model.

[0032] The carbon footprint generation unit (400) can estimate carbon emissions by inputting data transmitted in real time to the first carbon emission model. Accordingly, it predicts traffic congestion, weather, and driving routes that may occur on a specific road, as well as the resulting increase in energy consumption and carbon emissions.

[0033] Meanwhile, the artificial intelligence learning unit (900) uses external data such as the traffic flow data, climate data, and slope data as fixed data, and internal data such as driving speed, number of brake operations, acceleration, and air conditioner setting temperature as variable data to perform learning.

[0034] That is, artificial intelligence learning can be performed using both the aforementioned external and internal data as input data and energy consumption or carbon emissions as labels, and accordingly, a second carbon emission model is generated.

[0035] Afterward, the artificial intelligence learning unit (900) outputs the predicted energy consumption or carbon emission amount while modifying the internal data using the second carbon emission model. By repeating this process, the combination of internal data that minimizes the output for the fixed data is stored as optimal operation characteristic data.

[0036] In addition, the artificial intelligence learning unit uses external data as input data and performs artificial intelligence learning, such as deep learning, using the above optimal operating characteristic data as labels to generate an optimal operating characteristic model.

[0037] The above-mentioned route setting unit (300) searches for a driving route that minimizes energy consumption and carbon emissions by synthesizing data collected from the vehicle status detection unit (200), traffic flow analysis unit (700), climate analysis unit (750), carbon footprint generation unit (400), and geographic information system (GIS).

[0038] Specifically, the route setting unit receives the starting point and the destination point as input and searches for and sets the shortest driving route. At this time, the search can be performed while excluding constraints such as road types like toll roads and narrow alleys, and roads under construction.

[0039] In addition, the route setting unit sets a plurality of nodes on the driving route and calculates the slope between each node by detecting slope data through a geographic information system. At this time, the route setting unit can calculate the slope by receiving elevation data of a point matching the driving route using GPS and GIS data stored in the storage unit.

[0040] The carbon footprint generation unit (400) inputs slope data on the shortest distance driving path, traffic flow data received from the traffic flow analysis unit, climate data received from the climate analysis unit, etc., into a carbon emission model to output a predicted carbon emission amount.

[0041] In addition, the database is searched to detect the time-series path carbon footprint for each node, and the path carbon emissions corresponding to the current time of the node on the shortest distance driving path are detected.

[0042] The path setting unit compares the predicted carbon emissions and path carbon emissions with the corresponding setting values, and if at least one of the predicted carbon emissions and path carbon emissions is greater than the setting value, it changes the node and searches for a path smaller than the setting value again.

[0043] As a result of the search, if a route smaller than the set value is found, the driving route is changed to the found route, and if no route smaller than the set value is found, the driving route is changed to the route with the lowest carbon emissions. The changed route can be transmitted via the wireless communication unit (800) and displayed on the display unit of the vehicle.

[0044] The above driving feedback provider (500) transmits the vehicle carbon footprint generated by the carbon footprint generation unit (400) during operation to the vehicle via a wireless communication unit. Referring to FIG. 2, the display unit of the vehicle visually displays the amount of carbon emissions generated by the vehicle based on the vehicle carbon footprint transmitted from the driving feedback provider and the geographic information system, as shown in the lower section A.

[0045] In addition, the above-mentioned driving feedback provider (500) detects optimal driving characteristics at each node that minimize carbon emissions.

[0046] Specifically, the driving feedback provision unit (500) receives gradient data, traffic flow data, and climate data of the corresponding node and inputs them into the optimal driving characteristic model generated by the artificial intelligence learning unit (900) to obtain optimal driving characteristic data as output data.

[0047] In addition, the driving feedback provision unit can compare the driving characteristic data from the vehicle state detection unit with the optimal driving characteristic data, and if the difference is greater than or equal to a set value, it can display an alarm to the corresponding vehicle.

[0048] The above driving characteristic data is information regarding the operation of a vehicle and may include data such as vehicle speed, the number of times the brake is applied in a certain section, acceleration, and the set temperature of the air conditioner.

[0049] The above carbon emission rights request unit (600) performs a request to an external institution, such as a carbon emission rights exchange, to acquire carbon emission rights based on data generated by the carbon footprint generation unit (400).

[0050] Although the present invention has been described above with reference to embodiments thereof, those skilled in the art will understand that various modifications and changes can be made to the invention without departing from the spirit and scope of the invention as described in the following claims. Explanation of the symbols

[0051] 100: Vehicle Carbon Footprint Management and Analysis System 200: Vehicle Condition Detection Unit 300: Path setting unit 400: Carbon footprint generation unit 500 : Driving Feedback Provision Study 600 : Carbon Emission Allowance Request Department 700 : Traffic Flow Analysis Department 750 : Climate Analysis Department 800 : Wireless Communications Department 900 : Artificial Intelligence Learning Department

Claims

Claim 1 The system comprises: a vehicle state detection unit for detecting vehicle state data; a route setting unit for setting a driving route; a carbon footprint generation unit for generating a carbon footprint based on the state data; a database for storing vehicle carbon footprints and route carbon footprints; a traffic flow analysis unit for analyzing traffic flow data including traffic volume and average travel speeds of vehicles on the driving route and transmitting it to the carbon footprint generation unit; and a climate analysis unit for collecting climate data including precipitation, temperature, and humidity and transmitting it to the carbon footprint generation unit, wherein the route setting unit comprises the steps of: setting a minimum distance driving route; and setting a plurality of nodes on the minimum distance driving route. A vehicle carbon footprint management and analysis system using a geographic information system, comprising the steps of: inputting real-time traffic flow data between the nodes, climate data, and slope data detected from a geographic information system (GIS) into a carbon emission model to output a predicted carbon emission amount; detecting a path carbon footprint between the nodes from the database; comparing the predicted carbon emission amount and the detected path carbon footprint with a set value, and if at least one of the predicted carbon emission amount and the path carbon footprint is greater than the set value, searching for a path with a path carbon footprint smaller than the set value; and changing the driving path to the searched path. Claim 2 A vehicle carbon footprint management and analysis system according to claim 1, wherein the vehicle is an electric vehicle, and the carbon footprint generation unit generates a vehicle carbon footprint using battery consumption, charging data, and a carbon emission coefficient for the corresponding region received through the vehicle status detection unit. Claim 3 A vehicle carbon footprint management and analysis system according to claim 1, wherein the carbon footprint generation unit generates a path carbon footprint by summing the carbon footprints of each vehicle generated between the nodes. Claim 4 The vehicle carbon footprint management and analysis system according to claim 1 further comprises a driving feedback providing unit, wherein the driving feedback providing unit detects optimal driving characteristic data that minimizes carbon emissions for each node, and compares the driving characteristic data obtained from the vehicle state detection unit with the optimal driving characteristic data, and if the difference is greater than or equal to a set value, displays an alarm to the vehicle.

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