RFID based Logistic Management System using Internet of Things (IoT)

Proceedings of the 2nd International conference on Electronics, Communication and Aerospace Technology (ICECA 2018) IEEE Conference Record # 42487; IEEE Xplore ISBN:978-1-5386-0965-1

RFID based Logistic Management System using Internet of Things (IoT) Aishwarya Raj Laxmi M. Tech Student School of Electronics Engineering KIIT Deemed University Bhubaneswar, Odisha, India. E-mail: [email protected]

Ayaskanta Mishra Assistant Professor School of Electronics Engineering KIIT Deemed University Bhubaneswar, Odisha, India. E-mail: [email protected]

Abstract: In the era of IoT and data analytics this paper has proposed system architecture for RFID based shipment tracking using Raspberry Pi equipped with RFID RC522 module. Light weight MQTT protocol is used for publishing real-time passive RFID tag data to CloudMQTT broker from Raspberry Pi. Further the logistics management and monitoring can be done using web based multiple platform GUI using MQTT subscribe message from MQTT broker. Using data analytics tool various logistic related data can be automated for better logistic management. Raspberry Pi uses python based Mosquitto MQTT client program to publish data to CloudMQTT broker using an IEEE 802.11 Wireless LAN NIC.

This is done by RFID in which make the company aware of, where is the product. The main intention to develop a multimodality system is that it can be used for various applications.

Keyword: IoT, Logistic Management, Raspberry Pi, MQTT, CloudMQTT, Mosquitto, python, GUI, RFID, RC522

I. INTRODUCTION In this modern era, technology is important for success of an industry, as the market is more volatile, understanding the customer base and forecasting of demand has become more complex. This has pushed the companies to address the gap through various software applications and a review has been done to evaluate the feasibility of IoT in area of Logistic Management. IoT is a network of physical objects to exchange data with the manufacturer or the user [3],[12] which can also integrate identification, sensing and communication in that technology that has been used [4].Here things refer to unique identity of remote sensing, monitoring and self configuring [11].IoT technology and business strategy have influences on process of business and selected IoT application as it implies the interaction between digital and real world[8],[10]. Before reaching the customer, products should cross the multiple business partners to have right information about the identity, location, and other tracking information. This study helped us to bring the need of it in Transportation [9]. Also there should balance of time and money.

II. SYSTEM OVERVIEW It is evident that shipment tracking as well as visibility is very much required for logistic and financial interests of anyone included in the system. That is why the importance of shipment tracking comes into picture as it enables shippers to control the transportation system and location of freight also becomes easier at any point in its journey. The main aim is to increase product sales to end user and reducing both inventory and operating expenses [6]. This has helped for the performance of carrier, transportation costs and market trends so as to manage the logistics. It not only reduces costs but the process improves, gaining visibility and enhancing the overall performance. Also there is a better customer experience by minimizing delays. Another important module for our study is RFID. Radio frequency identification (RFID) uses electromagnetic field to automatically identify and track tags attached to objects which contains electronically stored information. Here we have used passive tag, collecting energy from readers near to it. The tag information is stored in a non-volatile memory. RFID is important to solve many business needs. For examples tracking pallets, cases, indication of products [5].With RFID in place which let the company know at what time exactly where a product is located physically within the logistic chain. Here each tag enables communication which is contact less with a valid reader device through a radio link by sending its corresponding unique ID[2],[5].RFID tags are mounted on locomotives to identify origin, destination of the commodities being carried. Hence RFID offers advantage over manual system allowing more efficient and reliable inventory and tracking of items [5].

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The main protocol used here is MQTT protocol. MQTT stand for message queue telemetry and transport is a light weight protocol to publish and subscribe system which is use to publish and receive message as a client. MQTT is a light weight application layer protocol most suitable for reduced power low data sensor networks. It also works on AWS cloud [7].All publish and subscribe control messages are sent to broker which get the data from publishing devices and forward it to subscribing devices. The mosquito broker is used in RPi [6].From the prospective of this work the MQTT protocols is implemented using two network technology. In the MQTT application layer protocol, message in encapsulated in TCP segments. The IEEE 802.11 is more complex suitable for high data-rate bandwidth longer range wireless communication, hence suitable for tracking at places where power requirement is more. Using the above modules the overall architecture has been planned such that, after various shipments the topic is published to the cloud MQTT and subscribed by the monitoring system of the office. The overall system architecture has been shown in Fig.1.

important. In shipment tracking the tracking is done in the warehouse, of when, the goods come in and out of the warehouse at a particular time stamp. The process of shipment in, shipment out is carried for a particular shipment id, scanner id of the product. Basically the average transit time is calculated to find the optimum route. Further the records can be maintained with least human interventions for transparency in logistic management and minimize operational cost. With reference to Fig.2 the basic model of shipment tracking has been explained. Here the RFID reader reads the information from the tag attached to the product and the information is sent to Raspberry Pi module where the processing occurs. Then the data is sent through WLAN which is MQTT publish unit where the information is published to MQTT broker which receives all messages and filters it and publish it to all subscribed clients. The information could be seen at front end GUI which can be android, mobile phone etc. The front end is interlinked with database as information can be stored and used in future also.

Fig.2: Model for shipment tracking

Fig.1: Overall system architecture

III. LOGISTIC MANAGEMENT: SHIPMENT TRACKING The proposed hetnet architecture is designed for generic IoT based application platform suitable for most of the real world IoT application with minor modification. The deployment of proposed architecture is done by designing a Python based gateway device using Raspberry Pi. The gateway module is subscribed to the same topic and whenever the user sends a command the information will be published to reply to the topic to which the gateway device is subscribed. Thus the command will be fetched by the gateway device. IEEE802.11 WLAN network is having higher transmission power and a higher data rate making it a good solution for the backbone, for the mentioned IoT deployment scenario [1]. In order to maintain transparency in the logistic between the customers, middle man and organizer the tracking of goods become

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Fig3.Algorithm for shipment tracking

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Fig.3 shows the proposed algorithm for the RFID based shipment tracking done using RC522 passive RFID Reader and the Raspberry Pi implemented using python. For shipment tracking the MQTT client is published/subscribed to MQTT broker using the RPi and it has been explained in Fig 4, such that when the IEEE 802.11 WLAN network using the MQTT broker publish and subscribe the topic, it is made available to the front end GUI. In MQTT terminology the server for MQTT protocol is broker or the channel between the two modules such that data can be published and subscribed at any point of time. The topic here is the tracking of goods such that the subscribed client will get the data immediately when then data is published. There can be multiple clients subscribing the same topic so that they can get a copy of received data from the MQTT broker. The process continues both way and tracking could be done easily.

IV. RESULTS The scope of the paper includes an implementation of proposed architecture as discussed in prior chapter. A. RFID RC522 based Shipment tracking with Raspberry Pi The proposed module for shipment tracking is an integral part of smart logistic management system. The module includes a RFID RC522 interfaced with Raspberry Pi using SPI protocol. The Raspberry Pi is equipped with a IEEE 802.11 WLAN adaptor to connect to CloudMQTT broker. The Raspberry Pi is running a mosquito MQTT client integrated using a python code.

Fig.6: Shipment tracking module using Raspberry Pi & RFID RC522

Fig4: MQTT Protocol-MQTT_publish and MQTT_Subscribe for shipment tracking

Also the schematic diagram as in Fig.5 shows the basic connection between RaspberryPi and RFID reader done for shipment tracking in this paper.

Fig 5: Schematic diagram of modules for shipment tracking

The python code is used to extract the UID of the passive RF Tag which is attached to the shipment as shown in Fig.6. The RC522 will read the card and pass the UID and other shipment related information to Raspberry Pi. B. Mosquito Client and CloudMQTT broker: The python code will do system call() and using mosquito MQTT client command publish the UID and timestamp to the CloudMQTT broker. Fig.7 shows a CloudMQTT Console Instant Information. Using this user authentication, Server Address, port number the Raspberry Pi can publish the UID and timestamp to the CloudMQTT broker. The major advantage of using CloudMQTT broker is it is being global and can be accessed from anywhere across the globe using simple internet connection. To retrieve the data from the CloudMQTT broker a simple cross platform (Linux, Windows) mosquito MQTT client can be installed at logistic company end. This mosquito MQTT client will subscribe the RFID topic which is created in the CloudMQTT instance. The RFID tag information which is published to the broker are forwarded to the company MQTT client. The data can be stored in a database and the company

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end. Various data analytics tools can be used to get mission critical information for the automated data generated by these MQTT based shipment tracking system.

V. CONCLUSION The proposed system architecture of an automated logistic management system is at the prototyping level for proof of concept. This can be further taken forwarded to product development level by using industry standard tools and software for full implementation of automation in logistic management for real-world use. Further work can be done on development of data analytics engine for the data sets available in this scope of the paper. VI. ACKNOWLEDGEMENT

Fig.7: CloudMQTT Console and Instant Information

The logistic company can implement such MQTT based RFID reader at the entry and exit point of their warehouse. The passive RFID tags are attached with the shipment, when a shipment passes the entry gate or exit gate the UID of the shipment can be scanned by RC522 and using MQTT publish it can be sent to CloudMQTT broker. The logistic company's central monitoring system is connected to CloudMQTT broker as a subscribed client to the particular topic. The topic names can be a warehouse location. What all shipments enter or exit a particular warehouse location can be updated to the logistic company monitoring centre database using MQTT publish and subscribed messages via CloudMQTT broker. Table.1: Automated Real-time data available for Smart Logistic Management using real-time shipment tracking Parameters Average time in transit from Warehouse ‘X’ to ‘Y’: Availability of TYPE-A shipment at Warehouse ‘X’: Shortest transit path for TYPE-A shipment: Fast moving transit path: Most demand shipment type: Average waiting time in warehouse for a TYPE-B shipment

Values 2 Days 3 hrs. 23 Mins 100 Numbers Nearest next available Warehouse ‘Z’ in terms of average transit time Warehouse ‘X’ to ‘Z’ TYPE: D 3 months 11 days 2 hrs.

Table.1 give an example of set of automated data that can be generated using different data analytics tools to extract more mission critical information for real-time shipment tracking. This automation can help the logistic company to track its shipments at its various warehouse locations without much human intervention which can cut down the operational cost and the reliability and availability of real-time data about their logistics by use of RFID based shipment tracking system.

The prototypes are developed in Wireless Communication & Networking Lab, School of Electronics Engineering, KIIT Deemed University. The schematic diagram of Raspberry Pi is designed using Fritzing. REFERENCES [1]

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