Localization of Sensor Nodes in WSN Using Area Between a Node and Two Beacons

Gautam, Prateek Raj; Kumar, Sunil; Verma, Akshay; Rashid, Tarique; Kumar, Arvind

doi:10.1007/978-981-32-9775-3_22

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…When location services are not enabled, but are connected to the internet through mobile network or Wi-Fi, offers can still be provided to the user, but on a more general level. RFM analysis will still be done based on the purchase history of the user and his/ her preferences, but the offer list generated would be pertaining to the region of the user instead of pin-point accurate results [23]. The Bluetooth beacons present within each shop is used to generate the discounts being offered to the products within each of their vicinities.…”

Section: User -Sidementioning

confidence: 99%

IoT Based Approach for the Increased and Improved sales for the Brick and Mortar Stores

Giridhararajan¹

2020

IJATCSE

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The consistent use of smartphones in daily life has brought the wave of online shopping and digital marketing into action. Over the last few years, brick-and-mortar store owners have increasingly seen consumers migrate away from retail stores in favor of convenient and quickly accessible digital outlets. Many shoppers feel that, with the ease of smartphone and "one-click" shopping, browsing for products in a physical store is almost obsolete. However, what if the very same technology that caused this crisis in retail industry could be used to drive customers into their stores? Bluetooth Low Energy (BLE) beacons provide a great way to guide customers through a larger store and find the intended product. In addition to customer convenience, beacons are a powerful tool for storeowners to deliver targeted product recommendations. Thus, the overall solution consists of two components -Proximity sensing and Product recommendation systems. When a customer comes into the proximity of a particular section of a store, the recommender system generates total and personal recommendation for the customer. The matching entries between recommended products and products from the particular section are the final optimized recommendation delivered to the customer via mobile application. Product recommendations are powered by the purchase history data of Future group stores. That way a new lease of life can be brought to struggling brick-and-mortar stores.

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Section: User -Sidementioning

confidence: 99%

IoT Based Approach for the Increased and Improved sales for the Brick and Mortar Stores

Giridhararajan¹

2020

IJATCSE

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“…Many applications like healthcare [1] and disaster response [2] benefited from the addition of sensing and networking. So, the common requirement of many WSNs systems is positioning and localization, where sensor nodes needed to discover their position according to the system design [3,4]. A localization is very simple in many cases where, some nodes covering small area, required a single hop communication and fixed number of gateways are involved [5].…”

Section: Introductionmentioning

confidence: 99%

Frugal Sensing

Ahmad

Jiang

et al. 2020

Proceedings of the ACM MobiArch 2020 the 15th Workshop on Mobility in the Evolving Internet Architecture

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The Node localization problem in the mobile sensor network gains much attention. Recently, parametric point selection adopted from the Loop division has produced great positioning accuracy in conventional settings. However, a state of the art solution suffers significantly when used in mobile-based network distinguish by a high degree of radio signal irregularity. Therefore, a novel localization algorithm is required to address these challenges. We have proposed a new localization scheme by deploying sensor motivated by frugality. The distance is computed by received signal strength (RSSI) in which localization is measured as a fuzzy multilateration scheme with the help of mobile anchor deployment. RSSI and the signal power is used as an input in a fuzification. The fuzzy toolbox of Matlab is used in the entire simulation process and compared with the state-of-the-art techniques. The simulation results demonstrate an overall improvement of 60 to 70 percent in the presence of high signal irregularity.

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