4.6 Article

ParcEMon: IoT Platform for Real-Time Parcel Level Last-Mile Delivery Greenhouse Gas Emissions Reporting and Management

期刊

SENSORS
卷 22, 期 19, 页码 -

出版社

MDPI
DOI: 10.3390/s22197380

关键词

IoT; greenhouse gas; sustainable logistics; last-mile emission; supply chain

资金

  1. Scope 3 Pty Ltd
  2. Swinburne University of Technology's Research Office

向作者/读者索取更多资源

Transportation is a significant contributor to greenhouse gas emissions in Australia, particularly due to the rapid growth of e-commerce and last-mile delivery. This study developed an IoT platform to measure and report on real-world last-mile delivery emissions. It analyzed the impact of various factors, such as vehicle characteristics, road conditions, and driving behavior, on emissions and found a trade-off between parcel weight and total distance traveled for emission reduction. The study demonstrated the feasibility of the IoT platform in collecting detailed emissions data at the micro-level, providing valuable insights for improving delivery processes and reducing last-mile delivery emissions.
Transport is Australia's third-largest source of greenhouse gases accounting for around 17% of emissions. In recent times, and particularly as a result of the global pandemic, the rapid growth within the e-commerce sector has contributed to last-mile delivery becoming one of the main emission sources. Delivery vehicles operating at the last-mile travel long routes to deliver to customers an array of consignment parcels in varying numbers and weights, and therefore these vehicles play a major role in increasing emissions and air pollutants. The work reported in this paper aims to address these challenges by developing an IoT platform to measure and report on real-world last-mile delivery emissions. Such evaluations help to understand the factors contributing to freight emissions so that appropriate mitigation measures are implemented. Unlike previous research that was completed in controlled laboratory settings, the data collected in this research were from a delivery vehicle under real-world traffic and driving conditions. The IoT platform was tested to provide contextualised reporting by taking into account three main contexts including vehicle, environment and driving behaviours. This approach to data collection enabled the analysis of parcel level emissions and correlation of the vehicle characteristics, road conditions, ambient temperature and other environmental factors and driving behaviour that have an impact on emissions. The raw data collected from the sensors were analysed in real-time in the IoT platform, and the results showed a trade-off between parcel weight and total distance travelled which must be considered when selecting the best delivery order for reducing emissions. Overall, the study demonstrated the feasibility of the IoT platform in collecting the desired levels of data and providing detailed analysis of emissions at the parcel level. This type of micro-level understanding provides an important knowledge base for the enhancement of delivery processes and reduction of last-mile delivery emissions.

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