RollCaller: User-friendly indoor navigation system using human-item spatial relation

Guo, Yi; Yang, Lei; Li, Bowen; Liu, Tianci

doi:10.1109/infocom.2014.6848234

Cited by 22 publications

(14 citation statements)

References 23 publications

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“…In [3], each customer is made of aware of the desired product using a RFID reader in smart phone and locate the object but this system works less efficiently when in crowd and obstruction increase. 3S-cart system is built using the WSN technology for obsonium carts to support smart obsonium.…”

Section: Literature Surveymentioning

confidence: 99%

Smart Cart Obsonium based on Secure System

M.D.*,

Khemnar,

Aher

et al. 2020

IJITEE

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Abstract: Nowadays IoT has its influence over every sector of life ,striving hard to improve quality of life. Obsonium is a never ending business and to improve the quality of obsonium we can take the help of technology. In today's technology, many companies are developing products that ensure convenience toward all people who needs a good obsonium experience from today ' s hectic obsonium which takes a lot of time for billing and getting out. Thus, we have developed a Smart Obsonium Cart, that allows faster check-out. First the product will have a RFID card which will filled first by shop Admin with other de-tails of the product. Then cart uses the RFID reader technology to identify the products details which is already available in the database. The total cost will be displayed on the mobile attached to the cart as and when the product is added to the cart. The user can view the details of the product on his mobile. IoT helps to design such a cart which will automatically scan the product and add the respective amount to be paid in the bill on our own smart phone itself. Technologies used in this system are RFID tags and RFID reader for fetching the price of each unique item. Arduino microcontroller to perform the sum of the prices of the products and to prepare the final bill. Mobile application for the final display of bill and the complete obsonium list. Security is provided by the weight scanner and validating the products bought to avoid tag tampering. All the item's information is stored in the cloud at first. Checkout verification is also done by passing the cart after payment through a lane with RFID readers.

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Section: Literature Surveymentioning

confidence: 99%

Smart Cart Obsonium based on Secure System

M.D.*,

Khemnar,

Aher

et al. 2020

IJITEE

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“…In recent years, RFID research has been greatly broadened along a number of directions: estimating the number of tags in a system through various statistical measurements that are functions of the number tags [2], [13], [26]- [29], [31], [32], detecting the missing-tag event probabilistically or pinpointing exactly which tags are missing [33]- [36], locating tags that are out of their original places [37], continuously collecting the IDs of tags in a dynamic system where tags are moving in and out [30], [39], using indoor RFID tags for localization or navigation purposes [7], [56]- [58], investigating the security issues presented to resource-scarce tags such as authentication and lightweight encryption [59]- [66], and searching a reader's interrogation zone to find the subset of wanted tags [67].…”

Section: Related Workmentioning

confidence: 99%

Tag-Ordering Polling Protocols in RFID Systems

Qiao

Chen

et al. 2016

IEEE/ACM Trans. Networking

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Future RFID technologies will go far beyond today's widely used passive tags. Battery-powered active tags are likely to gain more popularity due to their long operational ranges and richer on-tag resources. With integrated sensors, these tags can provide not only static identification numbers but also dynamic, real-time information such as sensor readings. This paper studies a general problem of how to design efficient polling protocols to collect such real-time information from a subset of tags in a large RFID system. We show that the standard, straightforward polling design is not energy-efficient because each tag has to continuously monitor the wireless channel and receive tag IDs, which is energy-consuming. Existing work is able to cut the amount of data each tag has to receive by half through a coding design. In this paper, we propose a tag-ordering polling protocol (TOP) that can reduce per-tag energy consumption by more than an order of magnitude. We also reveal an energy-time tradeoff in the protocol design: per-tag energy consumption can be reduced to at the expense of longer execution time of the protocol. We then apply partitioned Bloom filters to enhance the performance of TOP, such that it can achieve much better energy efficiency without degradation in protocol execution time. Finally, we show how to configure the new protocols for time-constrained energy minimization.Index Terms-Energy efficiency, polling protocol, radio frequency identification (RFID), time efficiency.

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“…In this part, we cover the state-ofthe-art techniques for data queries in indoor settings. There are indoor space queries intended for supporting efficient indoor navigation [4], [8], [9], [17], [18], [23], [38], [40]. Range queries [34], [53] and nearest neighbor (NN) queries [34] are used to find static indoor POIs.…”

Section: B Existing Researchmentioning

confidence: 99%

Indoor data management

Cheema

2016

2016 IEEE 32nd International Conference on Data Engineering (ICDE)

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A large part of modern life is lived indoors such as in homes, offices, shopping malls, universities, libraries and airports. However, almost all of the existing location-based services (LBS) have been designed only for outdoor space. This is mainly because the global positioning system (GPS) and other positioning technologies cannot accurately identify the locations in indoor venues. Some recent initiatives have started to cross this technical barrier, promising huge future opportunities for research organizations, government agencies, technology giants, and enterprizing start-ups -to exploit the potential of indoor LBS. Consequently, indoor data management has gained significant research attention in the past few years and the research interest is expected to surge in the upcoming years. This will result in a broad range of indoor applications including emergency services, public services, in-store advertising, shopping, tracking, guided tours, and much more. In this tutorial, we first highlight the importance of indoor data management and the unique challenges that need to be addressed. Subsequently, we provide an overview of the existing research in indoor data management, covering modeling, cleansing, indexing, querying, and other relevant topics. Finally, we discuss the future research directions in this important and growing research area, discussing spatial-textual search, integrating outdoor and indoor spaces, uncertain indoor data, and indoor trajectory mining.

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RollCaller: User-friendly indoor navigation system using human-item spatial relation

Cited by 22 publications

References 23 publications

Smart Cart Obsonium based on Secure System

Smart Cart Obsonium based on Secure System

Tag-Ordering Polling Protocols in RFID Systems

Indoor data management

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