scholarly journals A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250737
Author(s):  
Abdul Hannan ◽  
Faisal Hussain ◽  
Noman Ali ◽  
Muhammad Ehatisham-Ul-Haq ◽  
Muhammad Usman Ashraf ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fuel Saving ◽  
Hybrid Computing ◽  
Last Mile ◽  
Delivery Services ◽  
Computing Framework ◽  
Design Speed ◽  
To Come ◽  
One Time Password ◽  
Last Mile Delivery

The thriving adoption of drones for delivering parcels, packages, medicines, etc., is surging with time. The application of drones for delivery services results in faster delivery, fuel-saving, and less energy consumption. Giant companies like Google, Amazon, Facebook, etc., are actively working on developing, testing, and improving drone-based delivery systems. So far, a lot of work has been done for improving the design, speed, operating range, security of the delivery drones, etc. However, very limited work has been done to ensure a complete and reliable last-mile delivery from the merchant’s store to the hands of the actual customer. To ensure a complete and reliable last-mile delivery, a drone must authenticate the consumer before dropping the package. Therefore, in this work, we propose a consumer authentication (Consumer-Auth) hybrid computing framework for drone delivery as a service to make sure that the parcel is perfectly delivered to the intended customer. The proposed Consumer-Auth framework enables a drone to reach the exact destination by using the GPS coordinates of the customer autonomously. After reaching the exact location, the drone waits for the customer to come to the specific pinned location then it starts a two-factor consumer authentication process, i.e., one-time password (OTP) verification and face Recognition. The experimental results manifest the effectiveness of the proposed Consumer-Auth framework to ensure a complete and reliable drone-based last-mile delivery.

scholarly journals Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1833 ◽  
Author(s):  
Tamás Bányai
Keyword(s):  
Energy Efficiency ◽  
Supply Chain ◽  
Energy Consumption ◽  
Real Time ◽  
Real Time Scheduling ◽  
Improve Energy Efficiency ◽  
Increase Energy Efficiency ◽  
Last Mile ◽  
Time Scheduling ◽  
Last Mile Delivery

Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers

2014 ◽  
Vol 239 (2) ◽  
pp. 451-469 ◽  
Author(s):  
Yezekael Hayel ◽  
Dominique Quadri ◽  
Tania Jiménez ◽  
Luce Brotcorne
Keyword(s):  
Decentralized Optimization ◽  
Last Mile ◽  
Delivery Services ◽  
Last Mile Delivery

Matching Model for Multiple Delivery Methods in Last-Mile Delivery for Online Shopping

2021 ◽  
pp. 036119812110363
Author(s):  
Jianhui Du ◽  
Xu Wang
Keyword(s):  
Urban Areas ◽  
Online Shopping ◽  
Evaluation Criteria ◽  
Real Life ◽  
Matching Model ◽  
Delivery Methods ◽  
Analytic Hierarchy ◽  
Last Mile ◽  
Delivery Services ◽  
Last Mile Delivery

Against the background of e-commerce, online shopping has seen considerable growth in China, as in the rest of the world. The last mile of delivery services for online shopping is a logistics challenge that affects service performance. This study has two main aims: first, to construct an evaluation criteria system for last-mile delivery service; and second to propose a matching model, capable of ranking six delivery methods according to customer preferences in the different urban areas. The factors base is established from the literature and from questionnaires and interviews with experts. Moreover, by conducting a questionnaire with consumers and analyzing the data, this research identifies the top 15 factors. The matching model based on the fuzzy analytic hierarchy process is constructed to compute the weight of each factor. The collection of data on customer preference was performed in distinct urban areas. Finally, to illustrate the validity of the criteria factors and the matching model, it was applied to three districts in Chongqing in China. Finally, our theoretical results from the experiments in real-life instances show that the criteria system and the matching model could help express companies to identify appropriate delivery methods in specific areas.

scholarly journals A Roadmap to Nextgen Aircraft Control for Last Mile Delivery Drones

2021 ◽  
Author(s):  
Cesar Augusto Marcondes ◽  
Denis Loubach ◽  
Elton Sbruzzi ◽  
Filipe Verri ◽  
Johnny Marques ◽  
...  
Keyword(s):  
Decentralized Control ◽  
Cost Reduction ◽  
Smart Cities ◽  
System Of Systems ◽  
Aircraft Control ◽  
Speed Increase ◽  
Last Mile ◽  
Air Space ◽  
Delivery Services ◽  
Last Mile Delivery

<div>According to recent studies, unmanned aerial vehicles (UAV) can play a game-changing part in terms of cost reduction and speed increase to address the last-mile delivery (LMD) problem and also to attend emergencies. Last-mile delivery services are getting more and more relevant, especially when in times where social distance is required. Given this scenario, our paper introduces a cyber-physical (CPS) system roadmap propose applicable for last-mile delivery drones. The proposed CPS guidelines are based on the concept of system of systems to enable an emerging behavior towards smart cities’ governance. In this paper, we also discuss topics from air space control and reservation throughout communication infrastructure and decentralized control supported on a blockchain.</div><div><br></div>

Application of Drone in Solving Last Mile Parcel Delivery

2018 ◽  
Vol 6 (4) ◽  
pp. 302-319 ◽  
Author(s):  
Jiashi Liu ◽  
Zhongliang Guan ◽  
Jennifer Shang ◽  
Xiang Xie
Keyword(s):  
Energy Consumption ◽  
New Method ◽  
Combination Method ◽  
Delivery Method ◽  
Delivery Problem ◽  
Rural Town ◽  
Bright Future ◽  
Last Mile ◽  
Last Mile Delivery

Abstract The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem delivery method, 2) to compare the new method with the traditional TSP method in aspect of truck running distance, energy using and time occupation. The parcel delivery demand is sparse, so it is not dense enough for a truck to carry on delivery. We try to identify the best route for the drone to deliver the goods. We use k-mean method to carry on clustering, then we use enumeration method to fulfill the centroids delivery, which comes from the depot. We design a model and calculate the energy, time and distance saving between drone using method (DTSP) and traditional TSP method. The drone attended delivery saves truck delivery distance, energy consumption and time. The truck running distance of DTSP method saves 91.87%, the truck running distance is shortened from 189.69 km to 15.4252 km. The DTSP method saves 90.45% of energy. The DTSP method brings a 29.75% cutoff in time aspect when there are two drone in running. The research introduces the cluster and TSP combination method, which is a good way to carry on last mile delivery. The result shows a bright future for drone to attend parcel delivery. The e-commerce corporation can apply this method in practice.

scholarly journals Collaboration Model for Service Clustering in Last-Mile Delivery

2020 ◽  
Vol 12 (14) ◽  
pp. 5844 ◽  
Author(s):  
Seung Yoon Ko ◽  
Ratna Permata Sari ◽  
Muzaffar Makhmudov ◽  
Chang Seong Ko
Keyword(s):  
Market Share ◽  
Programming Model ◽  
Collaboration Model ◽  
Multi Objective Programming ◽  
Last Mile ◽  
Delivery Services ◽  
Service Clustering ◽  
Last Mile Delivery ◽  
Market Density ◽  
Express Delivery

As e-commerce is rapidly expanding, efficient and competitive product delivery system to the final customer is highly required. Recently, the emergence of a smart platform is leading the transformation of distribution, performance, and quality in express delivery services, especially in the last-mile delivery. The business to consumer (B2C) through smart platforms such as Amazon in America and Coupang in Korea utilizes the differentiated delivery rates to increase the market share. In contrast, the small and medium-sized express delivery companies with low market share are trying hard to expand their market share. In order to fulfill all customer needs, collaboration is needed. This study aims to construct a collaboration model to maximize the net profit by considering the market density of each company. A Baduk board game is used to derive the last-mile delivery time function of market density. All companies in collaboration have to specialize the delivery items into certain service clustering types, which consist of regular, big sized/weighted, and cold items. The multi-objective programming model is developed based on max-sum and max-min criteria. The Shapley value and nucleolus approaches are applied to find the profit allocation. Finally, the applicability of the proposed collaboration model is shown through a numerical example.

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