When

January 23, 2023    
12:00 pm - 1:30 pm

Bookings

Bookings closed

Where

Essex Hall Room 122
401 Sunset Avenue, Windsor, Ontario, N9B 3P4
Map Unavailable

The School of Computer Science is pleased to present…

 

Trustworthy Decentralized Last Mile Delivery Framework Using Blockchain 

 

MSc Thesis Defense by: Ala’ Alqaisi 

 

Date: Monday, January 23, 2023 

Time: 12:00 pm – 1:30 pm

Location: Essex Hall, Room 122

Reminder: If you attend, it is mandatory that attendance is logged in both the sign-in sheet and  QR Code.

 

Abstract:  

The fierce competition and rapidly growing eCommerce market are painful headaches for logistics companies. In 2021, Canada Post’s parcel volume peaked at 361 million units with a minimum charge of $10 per each. The Last-Mile Delivery (LMD) is the final leg of the supply chain that ends with the package at the customer’s doorstep. LMD involves moving small shipments to geographically dispersed locations with high expectations on service levels and precise time windows. Therefore, it is the most complex and costly logistics process, accounting for more than 50% of the overall supply chain cost. Innovations like Crowdshipping, such as Uber Eats and Amazon Flex, help overcome this inefficiency and provide an outstanding delivery experience by enabling freelancers willing to deliver packages if they are around. However, apart from the centralized nature of the Crowdshipping platforms, retailers pay a fee for outsourcing the delivery process, which is rising. Besides, they lack transparency, and most of them, if not all, are platform monopolies in the making.

New technologies such as blockchain recently introduced an opportunity to improve logistics and LMD operations. Several papers in the literature suggested employing blockchain and other cryptographic techniques for parcel delivery. Hence, this thesis presents a blockchain-based free-intermediaries crowd-logistics model and investigates the challenges that could harbour adopting this solution, such as user trust, data safety, security of transactions, and tracking service quality. Our framework combines a security assessment that examines the possible vulnerabilities of the proposed design and suggestions for mitigation and protection. Besides, it encourages couriers to act honestly by using a decentralized reputation model for couriers’ ratings based on their past behaviour.

 

Keywords: Last Mile Delivery, Crowdshipping, Blockchain, Threat Modelling, Reputation

 

MSc Thesis Committee:  

Internal Reader: Dr Xiaobu Yuan

External Reader: Dr Fazle Baki

Advisor: Dr Sherif Saad

Chair: Dr Shafaq Khan

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