Simulating the Effectiveness of an IoT Parcel Alert System for Enhancing Delivery Efficiency and Safety During Covid-19

Author:

Zainuddin Ahmad AnwarORCID,Mansor Hafizah,Badrulhisham Nurul Iffah,Zulkifli Nurul Nabilah,Mohd Ridzal Aisyah Afiqah,Ghazalli Nasyitah

Abstract

The Internet of Things (IoT) has revolutionized the way devices communicate and interact with one another. Malaysia has witnessed a substantial increase in online purchasing in recent years. The COVID-19 pandemic and the Malaysian government's mobility control order (MCO) have contributed to the rise in online sales. This circumstance has resulted in a substantial increase in the number of packages that Malaysian delivery firms must manage, producing issues for both homeowners and delivery services. Unattended parcel delivery, parcel loss, and unsuccessful delivery efforts have become widespread. This paper proposes an IoT-based Parcel Delivery Alert System to address the challenges associated with unattended parcel delivery, parcel loss, and failed delivery attempts. The system comprises a parcel safe box that integrates with IoT sensors, such as weight and load sensors, image sensors, and light sensors. The IoT sensors provide real-time information about the delivery status and alert the recipient once the delivery has been made. The system's efficiency and effectiveness were evaluated using the MARS simulator, demonstrating a significant improvement in parcel delivery performance. This paper presents the design, development, and simulation of an IoT-based Parcel Delivery Alert System that can enhance the delivery experience while minimizing delivery-related problems. The paper describes the design and development of the parcel safe box and the eventual evolution of the system. One can acquire access to the safe box by scanning the tracking number on the package's delivery label using a QR code.

Publisher

Penteract Technology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3