气候变化领域集成服务门户(CCPortal): Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data

CCPortal

DOI	10.1109/TIV.2021.3102400
	Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data
	Singh, Mukul; Dubey, Rahul Kumar
发表日期	2023
ISSN	2379-8858
EISSN	2379-8904
起始页码	768
结束页码	777
卷号	8 期号:1
英文摘要	Climate change is one of the greatest environmental hazards to mankind. The emission of greenhouse gases has resulted in a continuous increase in the temperature of the atmosphere leading to Global warming. CO2 continues to be the leading contributor to the greenhouse effect, with transport being a major CO2 emission source. The majority of transport emissions are from road transport i.e. vehicular emissions. To control vehicular emission, first, an efficient emission monitoring system is required. Direct sensor installation in individual vehicles is neither cost-effective nor the data is easy to collect. In this paper, a scalable vehicle CO2 emission prediction model is proposed which uses vehicle On-Board Diagnostics (OBD-II) port data. The proposed system uses real-time in-vehicle sensor data to estimate CO2 emission of the vehicle using a Recurrent neural network (RNN) based Long short-term memory(LSTM) model. OBD-II dongles can be used to easily transmit the vehicle's sensor data to the cloud, where the LSTM model uses this data to estimate the real-time CO2 emission of the vehicle. The proposed model provides a scalable and efficient system to monitor emissions at a vehicular level and, has been evaluated using public OBD-II dataset. The details of the data collection, sensors, and adapters used along with vehicle information are outlined in Section V-A.
英文关键词	Data models; Telematics; Sensors; Climate change; Predictive models; Real-time systems; Monitoring; Deep learning; Global warming; Hazards; Vehicle telematics; LSTM; RNN; deep learning; OBD-II; CO2 estimation
语种	英语
WOS研究方向	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000965701200001
来源期刊	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/281276
作者单位	Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Delhi
推荐引用方式 GB/T 7714	Singh, Mukul,Dubey, Rahul Kumar. Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data[J],2023,8(1).
APA	Singh, Mukul,&Dubey, Rahul Kumar.(2023).Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(1).
MLA	Singh, Mukul,et al."Deep Learning Model Based CO2 Emissions Prediction Using Vehicle Telematics Sensors Data".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.1(2023).