AU2020101681A4 - Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations - Google Patents

Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations Download PDF

Info

Publication number
AU2020101681A4
AU2020101681A4 AU2020101681A AU2020101681A AU2020101681A4 AU 2020101681 A4 AU2020101681 A4 AU 2020101681A4 AU 2020101681 A AU2020101681 A AU 2020101681A AU 2020101681 A AU2020101681 A AU 2020101681A AU 2020101681 A4 AU2020101681 A4 AU 2020101681A4
Authority
AU
Australia
Prior art keywords
laundry
terminals
management system
residence
centralized cloud
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
AU2020101681A
Inventor
Anita C.S.
Shiela David
Gokulkumari G.
Lalit GARG
Chinnadurai M.
Lakshmi Prasad M.
Varalakshmi R.
Rachna R.Chhajed
Murthy Ravaleedhar
Meivel S.
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
CS Anita Dr
David Shiela Mrs
M Chinnadurai Dr
M Lakshmi Prasad Dr
R Varalakshmi Dr
RChhajed Rachna Ms
G Gokulkumari Dr
Original Assignee
C S Anita Dr
David Shiela Mrs
M Chinnadurai Dr
M Lakshmi Prasad Dr
R Chhajed Rachna Ms
R Varalakshmi Dr
G Gokulkumari Dr
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by C S Anita Dr, David Shiela Mrs, M Chinnadurai Dr, M Lakshmi Prasad Dr, R Chhajed Rachna Ms, R Varalakshmi Dr, G Gokulkumari Dr filed Critical C S Anita Dr
Priority to AU2020101681A priority Critical patent/AU2020101681A4/en
Application granted granted Critical
Publication of AU2020101681A4 publication Critical patent/AU2020101681A4/en
Ceased legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/0835—Relationships between shipper or supplier and carriers
    • G06Q10/08355—Routing methods
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y40/00—IoT characterised by the purpose of the information processing
    • G16Y40/30—Control
    • G16Y40/35—Management of things, i.e. controlling in accordance with a policy or in order to achieve specified objectives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/0833—Tracking

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computing Systems (AREA)
  • Game Theory and Decision Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

CENTRALIZED CLOUD LAUNDRY LOGISTIC MANAGEMENT SYSTEM USING IOT ENABLED LAUNDRY TERMINALS IN RESIDENTIAL LOCATIONS ABSTRACT A centralized cloud-deployed to laundry logistic management system to handle massive data by using IoT is connecting the laundry terminals in residential locations. The terminals receive the orders from the residence, and through the gateway, it is sent to the centralized cloud. The big data is analyzed for logistics management, whereby using a dynamic algorithm, the shortest path for transportation is identified that takes minimum time and less cost. The currently received data mapped with the previous record. By deploying the machine learning algorithm, the workload or the mode of operation is also identified to obtain good quality. Once the laundry workload process completed, it is packed and delivered back to the residence by deploying updated real time delivery routing in logistics. IoT monitors the complete process from receiving the order, transporting the laundry to laundry service center, packing, and delivery back to the residence enabled smart devices like computer or mobile phone by the supervisor. It is completely automated to avoid errors and to get the information about the duration to complete the entire process maintaining privacy. 1 P a g e

Description

CENTRALIZED CLOUD LAUNDRY LOGISTIC MANAGEMENT SYSTEM USING IOT ENABLED LAUNDRY TERMINALS IN RESIDENTIAL LOCATIONS
Description
Field of the Invention.
The Field of the invention is related to IoT.
For services where vast data has involved, there is always a requirement of a massive data storage cloud. To extract the desired feature based on the requirement, it needs a machine learning technique with the completely automized application with JOT. Especially in this invention, the laundry logistics management system using the internet of things enabled laundry terminals in residential locations involves a centralized cloud. The requirements when received from the residence, using big data, the logistics system determines the route plan, vehicle for the laundry, and the duration. Using a machine-learning algorithm, the laundry process is completed, and again the logistics handle the packing and delivery to the residence.
Background of the invention.
There is always a need to have managed to interface the customer and the platform that performs a service. Today's world, where the self-service is lacking due to the busy schedule of the living, logistics plays a responsible role in handling the laundry service that not only saves the time but also meets the requirement with a neat and clean appearance.
In traditional laundry system, it involved a manual cleaning process and transportation. As the current world looks for privacy and security, there is a need to design a system that needs internet involvement in the application services.
Even there is a need to monitor the complete operation from the residence to the laundry service and back to the residence. It can be monitored by the supervisor using smart devices. It should be transparent, precise, and efficient.
Based on the characteristics of the distribution, the data mining technique was used. It can handle clusters of data, but still, to handle a large set of data, it is a challenging task.
There was an Optique platform model deployed, but still, it is not efficient. For vehicle routing, earlier, a mathematical model was deployed. But it is time-consuming, and it did not provide efficient service to the residence customer.
Later for solving problems with vehicle routing, Coppersmith-Winograd algorithm deployed to provide a heuristic approach. It is the algorithm involving matrix multiplication. Though it was an efficient method, as the customer increases, there is a decrease in precision.
Saving Mileage Heuristic Algorithm deployed provides the estimation of the path that gives an optimal solution. But its cost is more and also does not update in real-time.
1 P a g e
The classical routing of the vehicle method deploys a method of having a starting point and the destination point with minimized vehicle usage with minimal cost. Especially, Dijkstra's Shortest Path First algorithm is an efficient routing and scheduling method to find the shortest path in implementing the logistics management in real-time planning of the traveling path of a vehicle. It decreases collection time and delivery.
A dynamic algorithm that involves shortest path identification with minimum time for traveling and reduced cost for laundry is deployed in the cloud. The laundry parameter that has to be processed is merged with the previous entry of the customer in the cloud.
By adopting suitable washing modes for the specified model using a machine learning algorithm, the laundry process completed with good quality.
After completing the laundry process, again, the packing and delivery also handled by the logistics system to deliver laundry to the residence destination.
Objects of the Invention
The main object of the invention is to ease the laundry process with a transparent approach. This invention deploys a centralized cloud laundry logistic management system using IoT enabled laundry terminals in residential locations. The internet of things is deployed in laundry services where they can receive the customer order online. In a centralized cloud, by dynamic algorithm, the shortest path for logistics is identified, and the laundry is collected in minimum time and cost. The customer data is matched with the previous record of customer service. By using machine learning, the desired strategy is processed with good quality. The laundry is then delivered by implementing delivery routing with the real-time update in logistics.
Summary of the Invention
Residence services require the laundry process to be sophisticated, timely handling, secure with privacy, automated, transparent, and efficient. As the residents who involve in business or work having no time, and the older adults require laundry services to take care of a more frequent routine of their needs. The logistics management system handles this process using the internet for monitoring and process. The resident laundry is taken to the laundry center by the vehicle, and after cleaning, they are delivered back to the residence. A large storage device cloud is used to handle big data by using a dynamic algorithm to find the shortest path for transportation with reduced time and cost. It also merges the parameters of the customer with their previous records. The laundry center will perform the cleaning strategy by its characteristics modes of processing with good quality. By deploying delivery routing with real-time updates, the laundry is delivered to the residence. Smart devices monitor the entire operation over wireless internet by the supervisor at the terminals where the laundry order has been given.
Detailed Description of the Invention 2|Page
Fig.1 shows the process flow diagram of the laundry process from residence location. The logistics interface terminal with IoT enabled with smart devices receives all the laundry orders from the residence location. The request received, and the data information is sent to the cloud through a gateway. In the centralized cloud, from the big data that it has stored in the data storage, it schedules the laundry service and time for completion of the process and delivery. The vehicle is allotted to receive the laundry material from the residence and move it to the laundry center. It uses a dynamic algorithm to identify the shortest path to reach the residence and collect the material and reach the laundry service center. It is a vehicle routing technique deployed in managing vehicle logistics. The priority is also checked for any customer. When an order is received, it is also mapped with the previous record of the customer. After the big data analysis, the machine learning technique deployed to predict the mode of selection of operation of laundry service suitable for the material with good quality. The mode of selection is selected based on the characteristics of the material and also based on customer requests. The sequence of operations also tracked in the laundry service. Once the laundry service operation is completed, it is dispatched for packing. Once packing done, by deploying the real-time update delivery route, the logistics vehicle allotted to deliver the laundry to the residence. The supervisor monitors the complete process in the terminal and as well as the laundry service process using smart devices like computers or mobile devices.
Fig.2 shows the big data analysis in the centralized cloud that is IoT enabled laundry logistics management. Once the terminal receives the request, all the information and the process are analyzed in big data analysis. The vehicle is first allotted for the collection of the materials to be transferred to the laundry center for the process. The vehicle allotted has GPS not only helps to track the location of the vehicle status, but also the vehicle has a map to locate the residence at the earliest in the shortest path. For the identification of the shortest path with minimum time and cost, a dynamic algorithm is deployed. The resource is analyzed and allocated by big data analysis. It has an efficient wireless internet connection to connect between the terminal, the vehicle, the laundry service, and the customer to know about the status of the laundry process-the request when always received checks for the priority of the service to be completed first. The customer is also intimated regarding the status of the request and the duration of the laundry process before starting the laundry process. Even if the vehicle transportation path that was chosen earlier led to unexpected traffic, then the route can be rescheduled. If there are more number of laundry process runs at a time, the traffic management of the laundry process will handle the process, based on priority. The request, when received from the residence, it will always be stored in the data storage along with the previous record so that it will be a reference for the future.
3|Page

Claims (5)

CENTRALIZED CLOUD LAUNDRY LOGISTIC MANAGEMENT SYSTEM USING IOT ENABLED LAUNDRY TERMINALS IN RESIDENTIAL LOCATIONS CLAIMS We Claim:
1. A high-speed wireless internet connection for receiving the resident's order for laundry service and handle computing in laundry service.
2. Smart device to monitor the entire process online.
3. An efficient logistics management system with IoT enabled connected to laundry terminals.
4. A cloud receives the data through the gateway. It stores big data and deploys dynamic analysis to identify the shortest path for the vehicle routing to the laundry center and deliver back to the residents.
5. Machine learning deployed to select the washing modes with good quality.
1 P a ge
CENTRALIZED CLOUD LAUNDRY LOGISTIC MANAGEMENT SYSTEM Aug 2020
USING IOT ENABLED LAUNDRY TERMINALS IN RESIDENTIAL LOCATIONS
Drawings 2020101681
Fig. 1 Process flow diagram
1|Page
Fig. 2 Big Data Analysis
2|Page
AU2020101681A 2020-08-05 2020-08-05 Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations Ceased AU2020101681A4 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2020101681A AU2020101681A4 (en) 2020-08-05 2020-08-05 Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
AU2020101681A AU2020101681A4 (en) 2020-08-05 2020-08-05 Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations

Publications (1)

Publication Number Publication Date
AU2020101681A4 true AU2020101681A4 (en) 2020-09-10

Family

ID=72333679

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2020101681A Ceased AU2020101681A4 (en) 2020-08-05 2020-08-05 Centralized cloud laundry logistic management system using iot enabled laundry terminals in residential locations

Country Status (1)

Country Link
AU (1) AU2020101681A4 (en)

Similar Documents

Publication Publication Date Title
Pillac et al. A review of dynamic vehicle routing problems
CN107230014B (en) Intelligent scheduling system for terminal instant logistics
Sonneberg et al. Autonomous unmanned ground vehicles for urban logistics: Optimization of last mile delivery operations
Fikar et al. A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing
JP6823136B2 (en) Continuous delivery
CN104809601B (en) The mutual auxiliary system of express delivery based on electronic map
JP6211759B2 (en) Order management for liner delivery service
Li et al. Real-time vehicle rerouting problems with time windows
Ghiani et al. Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies
Ngai et al. Design and development of a context-aware decision support system for real-time accident handling in logistics
US20120259540A1 (en) Methods and systems for workforce management
Maciejewski et al. Large-scale microscopic simulation of taxi services
CN109635971A (en) A kind of people's goods is shared to use vehicle method of servicing
WO2017030998A1 (en) Planning of transportation requests
Baykasoglu et al. A multi-agent approach to load consolidation in transportation
WO2014145652A1 (en) Hybrid system and method for selecting and deploying field technicians in a facilities management hybrid workforce
CN109544070A (en) A kind of automatic logistics allocator
Abdelmagid et al. A comprehensive review of the truck appointment scheduling models and directions for future research
CN112308255A (en) Change-based reservation dynamic update automatic baggage handling system
Naumov et al. Model of the Delivery Routes Forming Process as a Service Provided by Forwarding Companies
Ninikas et al. Integrated planning in hybrid courier operations
CN105930245A (en) Method and system for monitoring service state of transaction terminal
CN109300335B (en) Flight time exchange system and method
KR20080080810A (en) System and method for planning of 3pl transportation network
Billhardt et al. Coordinating open fleets. A taxi assignment example

Legal Events

Date Code Title Description
FGI Letters patent sealed or granted (innovation patent)
MK22 Patent ceased section 143a(d), or expired - non payment of renewal fee or expiry