IoT-Based Smart Shopping Cart Using Radio Frequency Identification

Shahroz, Mobeen; Mushtaq, Muhammad Faheem; Ahmad, Maqsood; Ullah, Saleem; Mehmood, Arif; Choi, Gyu Sang

doi:10.1109/access.2020.2986681

Cited by 72 publications

(30 citation statements)

References 38 publications

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“…To eliminate waiting and queues time for bill payment, our system and Berdaliyev et al, 2016 [28] system used a reloadable card to perform the payment. Reducing the obstacles and difficulties for customers to find the product location by identifying its location, is developed only in our system and Shahroz, et al, 2020 [20]. Anti-Theft is incorporated in three system including our system.…”

Section: Comparisons With Existing Systemsmentioning

confidence: 99%

Smart Cart With Multi-shopping Solutions

Faisal

Awawdeh

Habte

et al. 2021

Int. J. Interact. Mob. Technol.

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Consumerism has constantly been growing, and visiting marketplaces and purchasing is a key development factor for the economic development of a city. The spending habits of people are a reflector of many development indices. As people go out for purchasing in malls for shopping essential items, they often tend to find long queues at the billing counter, and the queues are more longer during weekends and during sale seasons. This has been deterring people from going out shopping and instead resort to online shopping. This has affected the sales and revenue of departmental chains. Also, people spend quite a considerable amount of time searching through rows in order to find the items of their choice. Proposing a solution to these above-mentioned problems using technology is a real boon. Installing a payment option on the cart itself would result in cutting down the waiting times in queues. Moreover, the customers can also benefit from navigation through the virtual maps that would be displayed on the screens of the carts. This reduces the time wasted by customers in searching for products. Hence the customers are self-dependent during their shopping. For the retail group, their transactions and management are truly simplified with these developments. Additionally, the counter labor will decrease if not cease to zero, which in turn reduces the labor cost drastically. In times of pandemic like now, people have been sticking with online shopping due to various reasons, but they long to go out and spend time in the malls as they would in normal times. The proposed solution would definitely assist in the normalization of lives and bring back on-ground retail back to life.

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Section: Comparisons With Existing Systemsmentioning

confidence: 99%

Smart Cart With Multi-shopping Solutions

Faisal

Awawdeh

Habte

et al. 2021

Int. J. Interact. Mob. Technol.

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“…Mobile phone base station positioning is used to obtain the location information of mobile terminal users through the telecommunication mobile operator network. Indoor positioning includes Wi-Fi positioning, Radio Frequency Identification (RFID) positioning [4], and visual positioning of image acquisition by sensors. Currently, Wi-Fi positioning is a relatively mature technology with many applications.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Perception and Positioning Technology of Internet of Things by $K$ -Nearest Neighbor Matching Algorithm

Zou

Xingrui

Zeren

2022

Wireless Communications and Mobile Computing

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To study the intelligent sensing and positioning technology of the Internet of Things (IoT) combined with the K -nearest neighbor algorithm, the K -nearest neighbor matching algorithm and optimization algorithm are introduced using the indoor Wi-Fi positioning technology. The study proposes weighting K -nearest neighbor (WKNN) by weighted Euclidean distance, adaptive weighted Euclidean distance K-nearest neighbor Wi-Fi localization algorithm, and optimal K -value Wi-Fi fingerprint localization algorithm. The experimental error is verified. The experimental results show that the lowest error of continuous acquisition of 3 s signal values in experimental environment A is 1.8815 m, which is 10.13% lower than the error of only acquiring 1 s for the same K -value. The lowest error of environment B scheme two can reach 1.8862, which is 7.06% lower than the error of the same K -value. The optimal K -value Wi-Fi fingerprint positioning algorithm by distance constraint has better positioning accuracy than other KNN positioning algorithms, and the positioning fluctuation is smaller. The average positioning error of the optimal K in environment A is 1.2987 m, which is 0.2797 m less than the average of the traditional positioning algorithm. In environment B, the average positioning error of the optimal K is 1.5353 m, which is 0.3253 m less than the average of the traditional positioning algorithm. Therefore, the optimal K -value Wi-Fi positioning algorithm proposed has better performance.

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“…A secure authentication procedure for Drones and other IoT devices to identify the secure nodes and mitigate the identity-based attacks such as spoofing, etc. [13]. A robust access control method is required to prevent the unauthorized need to access the IoT resources [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

IoT-based Cyber-security of Drones using the Naïve Bayes Algorithm

Majeed¹,

Abdullah²,

Mushtaq³

2021

IJACSA

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Recent advancements in drone technology are opening new opportunities and applications: in various fields of life especially in the form of small drones. However, these advancements are also causing new challenges in terms of security, adaptability, and consistency. Small drones are proving to be a new opportunity for the civil and military industries. The small drones are suffering from architectural issues and the definition of security and safety issues. The rapid growth of the Internet of things opens new dimensions for drone technology but posing new threats as well. The tiny flying intelligent devices are challenging for the security and privacy of data. The design of these small drones is yet not matured to fulfill the domain requirements. The basic design issues also need security mechanisms, privacy mechanisms, and data transformations. The aspects like intrusion and interception in the domain of the Internet of Drones (IoD) need to be investigated to make these timely drones more secure and more adaptable. In this paper, we have used intelligent machine learning approach to design an IoT aided drone. This approach will provide intelligent cyber security system which will help in detecting network security threats using Blockchain.

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IoT-Based Smart Shopping Cart Using Radio Frequency Identification

Cited by 72 publications

References 38 publications

Smart Cart With Multi-shopping Solutions

Smart Cart With Multi-shopping Solutions

Intelligent Perception and Positioning Technology of Internet of Things by $K$ -Nearest Neighbor Matching Algorithm

IoT-based Cyber-security of Drones using the Naïve Bayes Algorithm

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IoT-Based Smart Shopping Cart Using Radio Frequency Identification

Cited by 72 publications

References 38 publications

Smart Cart With Multi-shopping Solutions

Smart Cart With Multi-shopping Solutions

Intelligent Perception and Positioning Technology of Internet of Things by K -Nearest Neighbor Matching Algorithm

IoT-based Cyber-security of Drones using the Naïve Bayes Algorithm

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Product

Resources

About

Intelligent Perception and Positioning Technology of Internet of Things by $K$ -Nearest Neighbor Matching Algorithm