On the use of the Internet of Things and Web 2.0 in inventory management

Abstract

Radio Frequency Identification (RFID) uses sensors to enable communication among things or objects in what is called Internet of Things (IoT) technology. Web 2.0 tools, on the other hand, are used on electronic devices (phones, PDAs, computers, etc.) to transmit data contents over the internet. In this study, we used a synergy of both technologies to enhance inventory control. We proposed software architecture which combined RFID and Web 2.0 tool advantages. The proposed architecture was used to develop an inventory management software prototype focused on enterprises in developing countries in Africa, specifically South Africa. The inventory management prototype was developed and was able to detect misplaced products and low stock levels, and send notification on Twitter to update inventory managers on mobile phone. Scalability measurements of the software were taken to validate the performance of the software prototype. The findings show that the system scaled reliably with increasing numbers of items read. The contribution of this work was compared to existing literature and our findings are presented in this paper. Real- life evaluation for a specific industry will be necessary to further reveal what improvements would be required to make this architecture more relevant. Behavioural study of users will also be required to further determine the economic and social benefits of this approach.

Keywords

Internet of Things (IoT)Radio Frequency Identifier (RFID)inventory management software architecture social network

1 Introduction

Information Technology (IT) provides ‘value to the firm by increasing internal and external coordinating efficiencies, and firms that do not adopt them may have higher cost structures and thus competitive disadvantage’ [35]. However, most technological changes are not always strategically beneficial, or guarantee success in business; in fact, they may lower the competitive advantage. ‘The use of IT alone has not produced sustainable performance advantages in the retail industry’ [35]. Large retailers use sophisticated inventory management technologies, including electronic data transfer, with suppliers to increase operational efficiencies and improve services. Information Technology is driving highly significant driver of inventory management. A large percentage of retailers in developing economies still use 1) scanners to log the receipt of goods, 2) point of sale (POS) to record purchases for accounting, marketing, and inventory management issues, and for taking physical inventories [3].

RFID technology has been used in many industries including the retail industry, food industry, livestock management, and supply chain management for a number of years. It has recently become a new and exciting area of research and is receiving much attention [3]. The major push started when the giant retailer Wal-Mart announced in 2005 that all its suppliers had to supply RFID- enabled shipments. RFID technology in a retail industry provides real-time replenishment of products, and does not require human intervention or line of sight to function [3, 5]. RFID technology is able to keep track of, and trace the location of products more precisely than other methods in current use, thereby potentially reducing losses. Wal-Mart stores which are RFID- enabled were 63 % more efficient in replenishing out-of-stock, leading to a 16% drop in out-of-stock problems [14].

The use of Web 2.0 within organizations is called Enterprise 2.0. Many retailers have noted the movement of some of the major web companies like Amazon, Yahoo, eBay and Google towards social and community features, and have noted the demand and interest this has created to consumers. Web 2.0 tools moved into enterprises to make positive impact in the organizations. Organizations are interested in using Web 2.0 practices mainly in two places. These are 1) within the business to advance competency and production, and 2) from the organization to customers to improve revenue and customer satisfaction [12].

In this research we addressed how Radio Frequency Identifier – Internet of Things (RFID-IoT) and Web 2.0 technologies can be utilized to improve inventory management systems in retail enterprises. The aim of this research is to develop software architecture for inventory management for enterprises that improves on traditional approaches. In achieving this goal, we analysed and developed a system which can fully integrate the technical advantages of RFID with Web 2.0 tools on a social medium such as the Twitter. The designed innovative architecture for managing inventory using RFID and Web 2.0 technologies was used to develop a software prototype. The performance of the prototype was evaluated on software scalability, and comparison with existing related studies was conducted and reported.

2 Related work

This section looks at the existing literature related to RFID-IoT technology and software architecture in the domain of IoT. The review considered the application of RFID-IoT in the pre- and web technology eras. We would like to emphasise how much the combination of RFID-IoT and Web technologies have improved access to real- time data. This shows the importance of this technology. Our review further reveals how and why the adoption of this hybrid technology in the developing nations has been slow and the need to accelerate adoption. We conclude the review with an analysis of relevant literature related to software architecture in the domain of RFID-IoT technology with an emphasis on how our work fills a gap in the existing work.

3 Impact of Radio Frequency technology for real-time data collection

Application of Radio Frequency (RF) technology in real-time data collection predates the web technology era. The works of Yao and Carlson [2], Eckles [29], Hornak [19], Harrington [36] and Forger [13] all reveal that RF technology impacted on transmitting real-time data before the explosion of the Internet. Over the years, real-time data access of inventory systems has been made easier with advancement in Internet and Web technologies. The combination of RFID-IoT and web technologies has brought about a tremendous improvement in real data collection [4 , 33]. Most of these studies have shown that internet usage in supply chain and inventory management has increased productivity, reduced costs and increased profit. Visich [21] investigated the actual benefits of RFID on supply chain performance through empirical evidence. The study discovered that the effect of automation on operational processes is the main benefit of RFID. This is closely followed by informational effects on managerialprocesses.

Bakker et al. [23] reviewed the new developments made on perishable stocks (deteriorating inventory) for inventory control from 2001 to 2012. The study showed that RFID facilitates integration down the supply chain, resulting in greater opportunities for inventory control of perishables. Chao et al. [4] shed light on RFID trends and contributions through a historical review and bibliometric analysis. From the analysis of the study’s findings, supply chain management (SCM), the health industry, and privacy issues emerge as the major trends in RFID. These studies on empirical data and case analysis revealed that RFID will be more ‘ubiquitously diffused and assimilated into our daily lives in the near future’ [4]. We expect this to happen to the African continent also. According to Upfold and Liu [8] South Africa is aware of RFID and hopefully will gradually utilize this technology. RFID vendors are becoming specialized in providing specific applications. Missions to roll out RFID applications in different countries are also on the rise. Supply chain, asset management and mining are amongst the areas expected to increase the demand for RFID applications, and actions in these areas are expected to increase in many other African countries.

3.1 Slow adoption of RFID-IoT in developing countries

In spite of the benefits associated with RFID-IoT and Web technologies adoption of this hybrid technology has been dismally poor, especially in developing countries [8 , 33]. Li et al. [33] explain RFID technical and implementation issues and how these issues can be addressed. Their study shows that research in the combined use of IoT and Web technologies is still very much in its infancy. Their findings were further supported by Brown and Russell [16] who conducted an exploratory investigation into RFID adoption in South African retail organisations and identified factors that have an impact on the adoption status. The findings show that, as at 2005, many retailers in South Africa had not yet adopted RFID or even conducted pilot studies, but intended to do so in the future. The situation had not changed significantly up till the time of conducting this research. There are hindering factors to the expansion of RFID technology. The most remarkable is the high cost of installing the application, particularly for low value volume products. The study conducted by Upfold and Liu [8] states that South African retail enterprises are aware of RFID technology and its advantages, but there are hindering factors, mainly poor tag read rates, accuracy, and lack of global standards. As a result, most retailers remained using barcode technology [16].

The research conducted by Pedroso et al. [25] in Brazil discovered minimal connection between anticipated benefits of adopting RFID technology and normal business challenges. A similar survey in South Africa by Brown and Russell [16] shows that the situation is not much different in Africa. Up-to-date empirical results have not been validated to reach this conclusion currently but observatory evidence at retail shops in South Africa is not different as most retail shops still do not use RFID technology as in 2010 [8]. Visich et al. [21] state that RFID implementation had not reached transformational level on either operational or managerial processes at the time of conducting their research. It is doubtful if the situation is any much different today especially in the context of our research.

However, RFID in South Africa has been marked as a well-established domain in some niche applications such as access control, e.g biometrics and tollgates [16]. The cost of tags is expected to drastically reduce as time goes by. This study sees this as a motivation to investigate the software architecture in the domain of RFID technology to implement novel applications for porting inventory information on social networks.

3.2 Software architecture in the domain of RFID-IoT

In agreeing that adoption of RFID-IoT technology remains in its infancy in most developing countries, Brown and Russell [16] did not say much about the need for enabling software platforms that would encourage this technology. In South African SME businesses ‘more than 85% rely solely on mobile phones for telecommunications’ [32]. Other studies have shown that about 90% of mobile phone users use their mobile phone for internet browsing, especially social media [15, 37]. This study opines, based on this evidence, that penetration of IoT technology in retail business, especially in developing African countries, will be accelerated if software content that business people would use to access the information is in abundance. Wong et al. [40] developed two systems for IoT technology, namely the Smart Dressing System (SDS) enabled by RFID technologies, and Intelligent Product Cross-selling System (IPCS).

A good number of applications of IoT technology in supply chain and inventory management and manufacturing exist [31, 38]. According to Lancioni et al. [31] the integration of the Internet into supply chain management applications has increased and has moved away from indiscriminate application of novel Internet technologies towards becoming a focused endeavour with precise expectations and measurable goals.

Existing research has placed much emphasis on elimination or reduction of inventory inaccuracies occasioned by theft, product misplacements, or transaction errors. In order to address the problem of shelf replenishment, Wong and McFarlane [9] provided a qualitative analysis of opportunities for improvement using RFID. The authors described the push/pull traditional replenishment processes. They described ‘an RFID-supported process characterized by automatic monitoring of stock levels and product movements as well as automatic compilation of pick lists on mobile devices’ among other contributions. These existing software applications for IoT have to a large extent not addressed real time shelf replenishment. Little attention has also been given to how to utilise existing web solutions to enhance inventory management in the IoT [13 , 39]. Our software architecture addressed this gap, as demonstrated in our design and experimentation.

4 Research methodology

This section introduces the methods and technologies used in the design of the proposed system with a discussion on how this model can enhance inventory management in retail enterprises. These technologies include Beachcomber, Arduino, Ethernet, HTTP, RFID reader/tags and Twitter. This study also revealed that there is an information flow gap on inventory processes when using IoT technologies, creating a need to enhance inventory management. To resolve this issue our model addressed the task of enabling bearer agnostic communication between humans and the objects of their interest and their business services.

4.1 Scenario illustration

For design clarity the following scenario was considered for inventory management in the retail industry:

Mr. Bongani is the inventory manager of XXZ Retails. He was having a meeting on 24 February, 2012 with his stakeholders. Mr. Bongani was still in his meeting with the stakeholders when he received the stock update tweet that: a) sugar stock was running low in the shop, b) some tea packets were misplaced in the milk products zone, and c) a certain item in stock needed to be removed from the shelves as it had expired. Mr. Bongani then conducted a sales analysis to discover the inventory status before corrective action was taken. He quickly sent an email to place orders for sugar with ABC suppliers. He then instructed the stock packers to move the misplaced items into the correct position. Finally, they were to remove expired items from the shelves. The manager continued with his meeting knowing that everything was under control. This provided the manager with the platform to monitor and manage inventory anywhere.

From this scenario, one can outline the significant requirements of inventory management systems in the retail environment. These are categorised into functional and non-functional requirements.

4.2 Functional requirements

Automated stock capturing and counting: Stock capturing is laborious and prone to human errors, and thus accurate automated, real-time stock capturing and counting is required. RFID readers and tags must work properly to capture product data.

Automated check-ups for damaged products: Alerts on expired or damaged goods to be removed from the shelves are generated to protect consumers and reputation of the retailer.

Awareness of stock levels on shelves: The Inventory management system (IMS) prototype sends an alert of product shortage on time, to notify the inventory manager to make the necessary decisions.

Awareness of misplaced stock: IMS identifies locations and quantity of misplaced stock.

4.3 Non-functional requirements

System scalability: In this environment, where thousands of products need to be tracked and analysed, the system needs to be capable of storing product information regardless of the size of the enterprise.

Response Time: It is absolutely necessary for the inventory manager to receive inventory updates in real time with no delays. The time it takes for a manager to receive updates must be less than a minute.

System trustworthiness: This task is vital; the IMS must provide reliable information to the user, with no delays that could jeopardise the inventory management.

System backup: System backup must always be up-to-date in order to mitigate system failure and use the inventory analysis for periodic reports to determine the growth of the business.

5 Description of technologies used

A brief description of the terminologies related to the technologies employed in this research is given in Table 1.

6 Model design and development

The overall functional requirements of the proposed architecture system must be met for reliability of the system. Figure 1 shows communication in Beachcomber for our proposed architecture.

HTTP is the resource adapter which sends information to beachcomber controller at http//:146.64.28.16:8080/beachcombservlet/inventory?msg=(). The Beachcomber controllers will route the information to the intended business service. The business service building block routes the information to the intended resource adapter, which is Twitter. The Twitter account must be created and its details must be saved in the service building block for routing of messages.

7 The proposed inventory architecture and implementation

This study proposes a monitoring system for inventory management enterprises to enhance visibility and effective use of information for the immediate decision- making process. The study proposes model to address the issue of unobserved misplaced and/or expired products on the shop shelves and late stock replenishment which can lead to lost sales. The use of Twitter plays a major role of notifying inventory manager in inventory changes which needs immediate attention. Figure 2 is the proposed architecture for monitoring inventory.

In this inventory management architecture, the RFID-enabled reader device reads RFID-tagged products and data is buffered to Arduino. Arduino allocates it’s time to the RFID product tags. The timestamp is the number of milliseconds that have elapsed since the exact time when the product was read. The data is sent with product ID and timestamp via HTTP over the Internet to the web browser (http://172.19.2.4). Data is extracted from the browser and sent to the database. The database will then be updated for changes to the inventory. Changes to the inventory are sent to Beachcomber via HTTP on (http://146.64.28.16:8080beacomber/inventory?msg=()). The URL links the database to the Beachcomber server. The Beachcomber controller will then connect to resource adaptors which route information to the intended business service, which is Twitter. The messages on inventory will be displayed on a Twitter page.

Figure 2 illustrates the architecture, which includes RFID, HTTP, Twitter, Arduino and Beachcomber. The system keeps the retailer informed on inventory process activities using Twitter. The endpoint device is made up of three boards – the RFID reader, the Arduino and the Ethernet device (for HTTP transmission). The reader device is an RFID tag reader. The reader is mounted in a fixed position. It reads RFID tags on products as the shelf rotates and sends data as HTTP messages to the Arduino buffer. In the system, the RFID-enabled shelf shown in Fig. 3 rotates for the RFIDreader to access the product information. Products are placed on the shelf according to product zones. For example, a sugar zone is for all sugar products, a milk zone for all milk products, etc. Each product zone has zone start and zone end tags. One cannot read the product ID before it comes to its product zone. In the database, all the product information messages are collected and sorted according to the timestamp.

The database holds the intelligence of what a particular tag means. For example, zone ID 000-00-AF-11 could be an identifier for the bread zone. The RFID-reader knows the zone it is in at any point in time from communicating with the database in the local server which holds information on the identities of the product zone delimiters. It sends the zone ID and timestamp to the database and advises it to retrieve the zone name for the zone ID. The database returns zone ID and checks if the product zone ID of the product is the same as the current zone ID. If not then the product is misplaced.

Example of the data structures for the zones and products are as follows:

ZONES

zoneID: 0000-00-AF-011 [RFID tag of the zone delimiter]

Zone Name: Bread

PRODUCTS

ProductID: 000-00-AR-BB-001 [RFID of the product]

ZoneID: 0000-00-AF-011

Product Name: Bread

The Arduino, which works with the RFID reader in the end-point device, stores the RFID-tagged products on the product shelves and provides the time in which the product was read. The product information, that is, the product ID and timestamp, is sent via HTTP protocol to the server that hosts the decision support system. The decision support system receives the product information in the form of HTTP messages. It forwards the HTTP notifications to Beachcomber. Beachcomber forwards the HTTP inventory notifications to Twitter as ‘tweets’.

The following can be said about the current technology:

RFID technology sometimes experiences poor read rates and poor accuracy [8].

In the smart shelf for inventory control the products need to be scanned first and the information stored in the database. In the laboratory experimental system, the shelf simulation consisted of a round wooden table top mounted with an RFID reader and zone delimiters. RFID tags are used as zone delimiters and mounted onto the table to categorise products and the RFID reader scans tags mounted onto products. This can reduce poor read rates.

The reader rotates at certain intervals to read the inventory status. When the table rotates the RFID reader detects all the delimiters and products in sequence. The system then retrieves information from the database and sorts the products according to their zones. If any product is found in a wrong zone, an ‘event’ is triggered. The system then sends a message to Twitter. A similar event is triggered when the product level on a shelf has reduced to a level at which more products need to be ordered. The user can view the updates on Twitter.

8 Prototype implementation

In the previous section the implementation model has been explained in detail. This section presents the experimental result when the system was tested.

8.1 Scanning of the products

The products were arranged on a revolving – Lazy Susan – table and read using RFID reader (Fig. 4). The Lazy Susan hardware rotates the table at certain time intervals; this is done to keep track of inventory status during the day to make necessary arrangements in time.

Figure 4 shows the table with products; the table rotates and passes by the reader which scanned the products. The reader was connected to the local server with an Ethernet cable.

8.2 Data on the web browser

The data captured by the RFID reader appears on a web browser. It is sent via HTTP. This data has an Arduino timestamp on the left and product ID on the right. The data is then extracted from the web browser to the database for processing.

The first scan records the data about product on a text (.txt) file. The data on the.txt file is the record of the initial stock in the shop. Figure 5 shows the temporary.txt database used to save product and track the changes. The.txt file was used for quick loading of data over the internet and data cannot be erased or deleted once it is saved. It is also efficient for this study as inventory needs to be updated frequently. The second scan updates from this.txt file to track changes in the inventory. The inventory record on the database does not change unless the inventory manager is loading new stock and new inventory records are created.

Figure 6 is an example display of changes recorded in the inventory. It shows the scans where some products were misplaced, and low stock. For testing purposes, items were swapped around to illustrate misplaced products. To test the stock level some items were not scanned. In Fig. 6, only 6 product items were scanned and 3 delimiters were used to categorize them according to their zones. The system updated the inventory record on the database to track changes and sent notifications to the Twitter page. The system counted the number of all products and detected products which are not in their zone, and at low stock levels. In the tea zone, 4 items are on shelf and 1 item, which is milk, was misplaced. In the milk zone, only 1 item is available, which means milk stock is low and replenishment is required. Sugar stock is low, only one item is available and it is not misplaced. The tea stock count is 3. The product summary interface must display on the twitter page the product items in detail, the counts of misplaced, and the level of stock in the shelves.

8.3 Notifications on twitter

Figure 7 shows the notifications appearing on Twitter to update the inventory manager. The inventory tweets alert the inventory manager to: milk stock, sugar stock running low on shelves, and milk misplaced in the tea zone. These notifications were fed into Twitter in real time.

9 Prototype evaluation

9.1 Software scalability evaluation

Scalability evaluation of the proposed system was measured by reading the time taken when a certain number of RFID tags was read. The Arduino time is in nanoseconds, and 20 items were scanned in 4s. Results indicated that as the number of tags read increased, time taken increased also. However, when 4 tags were scanned, it took a longer time than expected. This shows that the system scalability rate was not constant with time. However, the time taken to read items remained fairly constant after four items up to a maximum of 20 items read. This shows that the system scaled fairly well with multiple item read reaching a threshold at the reading of four items. Figure 8 shows the scalability graph when the times taken to detect misplaced items and send notifications to Twitter were taken. The system was quicker to identify the first 3 items that were misplaced. The threshold at the point of reading 4 items is 800 nanoseconds. The time taken to read misplaced items reached a peak of 900 nanoseconds for reading all 20 items used. However, the time is in nanoseconds, which is apparently a quick feed to Twitter for human detection. The table below shows the times corresponding to the number of misplaced items being read using RFID tags.

10 Inventory management implications on RFID and twitter usage

Existing research outputs have concentrated to a large extent on the use of RFID or IoTs in inventory management with little emphasis on the performance of software that communicates these real time data [1 , 36]. Existing software solutions have concentrated on customised applications with little attention on how to utilise existing web solutions to enhance inventory management in the IoT [13 , 40]. The social network platform is used by almost every mobile internet user today. It is much more user friendly and convenient for an average user to receive and transmit contents over the social network media such as Facebook, Twitter, YouTube etc. The proposed model in this research enhances existing studies by providing a novel application of RFID with social Internet technologies to provide better real time shelf information for stock replenishment. However, the IoT technology has drawbacks though in developing countries like South Africa, to fully utilise the benefits of this study, many tasks will need to be taken into consideration. This includes training of the staff, cost of the technology, complexity, its ambiguity and other implications involved in sustaining this technology, e.g. security issues. Another limitation, as noted in other studies, is that ‘RFID is not the ideal identification technology where ferrous materials need to be tracked’ [9]. The reason for this is that ‘the electro-magnetic shielding properties of such materials as well as the de-tuning of the antenna circuits imbedded in the tags’ prevents the reader from accurately receiving data from the tag. For these reasons, this research can be extended ‘to incorporate optical markers as replacements for RFID in certain applications’ [4]. Similarly, volatile liquids are not well suited for RFID because of the risk of explosion [8, 34]. This causes the uncertainty for big retailers to adopt the technology. The South African retail industry is aware of the RFID technology, but is merely sceptical and adopting a wait-and-see approach.

11 Conclusion

This research proposed and prototyped a just- in- time architecture for inventory control that utilises RFID and Web 2.0 technologies. The result of the prototype was evaluated. The proposed inventory management system was able to provide timely information required by an inventory manager over a social network medium. The two tasks, to notify inventory manager of misplaced stock and low stock levels on shelves were accomplished. Twitter notifications on inventory were received in real time. This study demonstrates how enterprises can benefit from using the Internet of Things (using RFID technology) with web 2.0 tools (using social networks) to improve inventory management. This study is a real and feasible business application in retail enterprises. Thus we advocate rapid development of our concept in enterprise inventory management.

The work also evaluated the developed prototype application to determine the scalability of its performance in the event of increasing load of tasks. The scalability result (Fig. 8) shows that optimum utilisation of the prototype system needs a minimum of five items read. As a result of laboratory experimental constraints, only 20 items were used to test the system. The experiments show further that the performance of the system does not degrade with accessing the maximum number of items.

The prototype implemented was simulated in a room environment, which gives the idea of what can happen in a real world inventory using Twitter. However, when the system is implemented in real life, it is not certain that the system will scale as effectively as in this simulation. This is due to the immensity of the data involved in real life applications which may not be the case with simulation. For instance, only a sample of 20 items was used in the simulation and also the use of social medium as channel of communicating business information may raise security concerns such as information leak to competitors. Furthermore the inventory status notification on twitter serves as an immediate notification to managers regarding stock status, further analysis for this information hasn’t been investigated yet.

Footnotes

Acknowledgments

We wish to acknowledge the equipment used at the CSIR Meraka unit and their research funding. The first author appreciates researchers and the insightful discussion they had on the Internet of Things.

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