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Debajyoti Biswas

Bio: Debajyoti Biswas is an academic researcher from Jadavpur University. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 1, co-authored 7 publications receiving 51 citations.

Papers
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Proceedings ArticleDOI
01 Dec 2017
TL;DR: This work used two NodeMCU (ESP8266 WiFi module) which is a easily programmable which acts itself as a sensor node and used RSSI technique to determine the distance between two nodes.
Abstract: The use of WiFi is now a part of each human life. Airports, railways, bus-stand, home, markets everywhere now people uses WiFi because its reliability and low-cost. WiFi is also applicable in future tech of IoT (Internet of Things). In this work we used two NodeMCU (ESP8266 WiFi module) which is a easily programmable. NodeMCU which acts itself as a sensor node can be used as Access Point (AP) or as a STAtion (STA). We used one node as a AP and another as a STA. To locate a device distance measurement one of most important issue. There are lots of technique to find out the distance between two nodes (e.g. Time of Arrival (TOA), Time Difference of Arrival (TDOA) or Received Signal Strength (RSS) algorithms etc). In this work we use RSSI technique to determine the distance. First, we take around 300 sample data (RSSI values) and find the standard deviation to calculate how much the RSSI values are spread out and use curve fitting technique to find suitable equation for estimate distance. Then, we compared the estimated distance with actual distance to find the error level in percentage. We are success to reduce the average error level up to 8.32%.

79 citations

Journal ArticleDOI
TL;DR: In this article , the authors proposed a game theory model in a supply chain (SC) involving one manufacturer and one retailer, and found that high levels of distrust push firms to avoid the implementation of blockchain.

26 citations

Proceedings ArticleDOI
11 Feb 2021
TL;DR: In this article, a new localization scenario on distributing the coverage area based on the received signal strength indicator (RSSI) was investigated, where the base station (BS) will track the target vehicles.
Abstract: The physical position of the vehicles is vital information for the tracking operation. The vehicles localization have several benefits and support for safety, comfort, and reliability in future transportation systems. Thus the vehicular localization has investigated, where the base station (BS) will track the target vehicles. This paper mainly addresses a new localization scenario on distributing the coverage area based on the received signal strength indicator (RSSI). The RSSI measured in regular operation and consume minimum energy. However, wireless RSSI suffers from various interference in dynamic environments. For solving these issues, several methods have been proposed in the literature, including the signal intensity attenuation model (SIAM). This paper incorporates the fact that the motion of vehicles satisfies environmental constraints to improve the accuracy of RSSI-based localization by a new model, namely the gaussian signal attenuation model (GSAM) using most likely RSSIs. Numerical results demonstrate that the proposed method considerably outperforms the existing methods in terms of dynamic positioning accuracy.

9 citations

Proceedings ArticleDOI
18 Dec 2020
TL;DR: Experimental results demonstrate that CFT provides a better estimation than other existing models, and proposes a method by curve fitting technique (CFT), which reduce error to an extreme limit.
Abstract: In our modern society, WiFi (wireless fidelity) is an essential part of human life because every smartphone builds with WiFi facilities. Due to the requirement for WiFi, the wireless sensor networks (WSNs) gaining its maturity and the data traffic demand has also increased. Therefore, the problem of network localization became more challenging. For any uncertain position localization by the signal strength, the received signal strength indicator (RSSI) is a crucial benchmark. The localization process using RSSI is simple as well as cheap than any other existing methods. At the time of the internet of things (IoT) applications, WiFi can use as a leading access technology. Thus we focused on the localization using the cheapest WiFi module NodeMCU (ESP8266), which is easily programmable and operate on 2.4 GHz frequency bands. For position estimation, two modules have used, one as an access point (AP) and another as a station (STA). In the present literature, a lot of techniques have discussed to reduce the error level. However, most of them cannot achieve significant accuracy. Therefore, in this work, we proposed a method by curve fitting technique (CFT), which reduce error to an extreme limit. Moreover, we observed the error in three circumstances, i.e. outdoor, corridor and indoor. Experimental results demonstrate that CFT provides a better estimation than other existing models.

3 citations

Proceedings ArticleDOI
16 Dec 2020
TL;DR: In this article, the authors proposed an RSSI-based localization scheme that considers the trend of RSSIs obtain from the AP to estimate the positions of stations (STAs), i.e., sensors.
Abstract: The sensors’ geographical position is vital information in wireless sensor networks (WSNs) required for tracking, target detection, controlling, and monitoring systems. Thus 10-calization is an essential matter in WSNs. Localization methods are classified into two categories, range-based and range-free. Range-based localization achieves higher accuracy using received signal strength indicator (RSSI) values compare to range-free approaches, which obtain lower efficiency. RSSI produces a convenient process to find sensors’ positions because of the energy constraints of hardware in sensors. However, for the channel noise, fading, and shadowing, it is not possible to calculate the actual locations. In this paper, we introduce an RSSI-based localization scenario that considers the trend of RSSIs obtain from the Wi-Fi access point (AP) to estimate the positions of stations (STAs), i.e., sensors. Through applying the curve fitting technique (CFT), we estimate the relationship and choosing the best perfect curve the relation is established. The error level can significantly reduce by selecting the best accurate curve. Simulation demonstrates that the proposed localization scheme achieves higher positioning accuracy compared to a broad range of localization approaches.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: The surveying of recent research in this area can support a better understanding of smart-city solutions based on popular platforms such as Raspberry Pi, BeagleBoard and Arduino, as presented in this article.
Abstract: With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.

40 citations

Journal ArticleDOI
TL;DR: This study aims to conduct a comprehensive blockchain analysis with a bibliometric study based on the analysis of 1842 documents published in the 2007–2021 period using Scopus, and generates three main groups of six clusters.
Abstract: Blockchain technology remains popular for several reasons. The main one is that it has facilitated the rise of digital currencies over the past several years and many other uses of non-crypto currency. There is a belief that the technology itself could far exceed cryptocurrencies by its impact. Thus, researchers are still discovering the real potential of blockchain. This study aims to conduct a comprehensive blockchain analysis with a bibliometric study. The data was retrieved from the Scopus database and was analyzed using the VOSviewer software, developed at Leiden University’s Centre for Science and Technology Studies (CWTS), Leiden University, the Netherlands. The study is based on the analysis of 1842 documents published in the 2007–2021 period using Scopus. From the visualization, three main groups of six clusters are generated. The red area includes topics related to blockchain technology, supply chain management, and sustainable development. The green cluster stands for such keywords as blockchains, smart contracts, electronic money, and Bitcoin and Ethereum. The blue cluster area focuses on issues related to artificial intelligence, big data, health care, and COVID-19. The analysis helps to improve the quality of the review by directing researchers to the most significant documents and mapping areas of publications.

29 citations

Journal ArticleDOI
TL;DR: This is the first empirical work to evaluate the benefits emerging from incentives, which can activate smart contracts in the blockchain and enable active return approaches in CE, a dual circular system composed of a CLSC and a reverse omnichannel.
Abstract: PurposeThis paper aims to analyze the benefits of the blockchain to the circular economy (CE), which is composed of both closed-loop supply chain (CLSC) systems and reverse omnichannel solutions. By ensuring transparency, traceability, visibility and security, the blockchain allows firms to acquire operational capabilities through a CLSC and service capabilities through a reverse omnichannel, which can boost business performance considerably. The related network of relationships can be reinforced by establishing incentives, which entail both smart contracts in the blockchain and active return approaches in CE.Design/methodology/approachAfter identifying the boundaries of the theoretical framework, several research hypotheses are developed according to the literature review and emerging gaps. These gaps link to the impact of the blockchain on CE systems (CLSC and reverse omnichannel), as well as the influence on business performance. The hypotheses are then tested using structural equation modeling and adopting a partial least squares-path modeling technique on a dataset composed of 157 firms. Finally, multigroup analysis is used to test the impact of incentives on the research hypotheses.FindingsThe blockchain facilitates a more efficient CE system, although reverse omnichannel solutions seldom bring any benefits to performance. The shift from a passive to an active return approach must be carefully evaluated. The CLSC network can benefit from an active return approach by developing appealing incentives for collectors and enhancing the positive effects of the blockchain. In contrast, consumer incentives can have detrimental effects on the blockchain. Various combinations of incentives can only bring a few business performance increases, while collector incentives are vital to reinforce the CE system's operational and service capabilities.Originality/valueThis paper takes a new approach toward the study of CE, which considers a dual circular system composed of a CLSC and a reverse omnichannel. The research explores whether the adoption of blockchain technology enables better return processes by improving the operations in CLSC and services in reverse omnichannel. Finally, this is the first empirical work to evaluate the benefits emerging from incentives, which can activate smart contracts in the blockchain and enable active return approaches in CE.

28 citations

Journal ArticleDOI
TL;DR: In this paper , the authors explore the link between digitalization and sustainable business models, illustrating the main potential impacts of digitalization for each block of SBM and propose a list of the potential benefits that digitalized SBMs can bring.

19 citations

Journal ArticleDOI
TL;DR: This work presents the People Mobility Analytics (PmA) solution, which collects probe requests generated by Wi-Fi devices when scanning the radio channels to detect Access Points and processes the collected data to extract key insights on the people mobility.

16 citations