Unsupervised Crowd-Assisted Learning Enabling Location-Aware Facilities

Sikeridis, Dimitrios; Rimal, Bhaskar Prasad; Papapanagiotou, Ioannis; Devetsikiotis, Michael

doi:10.1109/jiot.2018.2810808

Cited by 39 publications

(22 citation statements)

References 37 publications

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“…In the past few years, Bluetooth-based indoor localization had been extensively studied for IoT, mostly based on fingerprint-based techniques. Sikeridis et al [190] proposed an unsupervised crowd-assisted learning enabling locationaware facility by using RSS of Bluetooth low energy beacons. They designed a three-layer location-aware infrastructure from which many moving clients can provide data from a sensing layer.…”

Section: ) Rfid-based Positioning Systemmentioning

confidence: 99%

“…Note that the fingerprints construction is a laborious task in indoor positioning, and it is always difficult to obtain enough label fingerprints for positioning. To overcome the bottlenecks, crowdsourcing [84], [112], [113], [190] and other calibrationfree [49], [95], [277] techniques are two candidate strategies in easing the burden of data collection in the offline phase. Crowdsourcing resorts to other clients to automatically sending their positioning data to a server, and thus greatly reduces the site-survey fingerprint construction work.…”

Section: A Lessonsmentioning

confidence: 99%

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A Survey on Fusion-Based Indoor Positioning

Guo

Ansari

et al. 2020

IEEE Commun. Surv. Tutorials

191

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Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusionbased positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future. Index Terms-Indoor positioning based services (IPS), fusion-based positioning, complex electromagnetic environments (CEEs), ensemble learning.

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Section: ) Rfid-based Positioning Systemmentioning

confidence: 99%

Section: A Lessonsmentioning

confidence: 99%

A Survey on Fusion-Based Indoor Positioning

Guo

Ansari

et al. 2020

IEEE Commun. Surv. Tutorials

191

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“…In this hybrid scheme, an efficient global-local interaction reduces the task complexity drastically. In [11], a location-aware infrastructure is proposed to combine a broad sensing layer, centralized cloud federation support, and edge computing. With the sensing capability of mobile devices, users can obtain the crowd sensing services in IoT.…”

Section: Related Workmentioning

confidence: 99%

“…is probability is determined by the partition value N. Hence, the proper value of N will result in the maximized completed probability. We solve this problem based on equations (10) and (11) and obtain the optimal value N * to maximize the completed probability, which means optimal partition is obtained. □ 4.2.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…Total mobile workers' arrival rate λ r Delay requirement D i Task load Ta i Monetary reward R i to a worker Mobile workers' computing capacity B Output: e optimal task partition N * and the maximal value P i (N * ) (1) Based on equation (1), STa i (N) ⟵ Each subtask load (2) Based on equation (3), P iw ⟵ e probability that worker w accepts the subtask of task i (3) With P iw , transition probability matrix Q is obtained based on Equation (8) (4) Based on equation (5), SD i ⟵ Duration for each worker to complete a subtask (5) Based on equation (7), m ⟵ e number of slots within D i − SD i (6) Within m slots, P i (N) is obtained based on equation (9) (7) Using equation (10), N′ ⟵ the optimal task partition in theory (8) Using equation (11), N * ⟵ the practical optimal task partition (9) Based on equation (9) and N * , P i (N * ) ⟵ the maximal value of successful assignment probability Return N * and P i (N * ) ALGORITHM 1: Optimal task partition for task i.…”

Section: Inputmentioning

confidence: 99%

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Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

Zhai

Wang

2019

Wireless Communications and Mobile Computing

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Mobile crowdsourcing takes advantage of mobile devices such as smart phones and tablets to process data for a lot of applications (e.g., geotagging for mobile touring guiding monitoring and spectrum sensing). In this paper, we propose a mobile crowdsourcing paradigm to make a task requester exploit encountered mobile workers for high-quality results. Since a task may be too complex for a single worker, it is necessary for a task requester to divide a complex task into several parts so that a mobile worker can nish a part of the task easily. We describe the task crowdsourcing process and propose the worker arrival model and task model. Furthermore, the probability that all parts of the complicated task are executed by mobile workers is introduced to evaluate the result of task crowdsourcing. Based on these models, considering computing capacity and rewards for mobile workers, we formulate a task partition problem to maximize the introduced probability which is used to evaluate the result of task crowdsourcing. en, using a Markov chain, a task partition policy is designed for the task requester to realize high-quality mobile crowdsourcing. With this task partition policy, the task requester is able to divide the complicated task into precise number of parts based on mobile workers' arrival, and the probability that the total parts are executed by mobile workers is maximized. Also, the invalid number of task assignment attempts is analyzed accurately, which is helpful to evaluate the resource consumption of requesters due to probing potential workers. Simulations show that our task partition policy improves the results of task crowdsourcing.

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Industry 4.0 Data-Related Technologies and Servitization: A Systematic Literature Review

Zambetti¹,

Pinto²,

Pezzotta³

2020

IFIP Advances in Information and Communication Technology

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The advancements and adoption of digital technologies enable manufacturers to approach intelligent production and reach a higher level of automation in the wave of Industry 4.0. Even though manufacturing is at the center of this industrial revolution, the impact of digital technologies is more far-reaching: indeed, one of the biggest growth potentials is recognized in the paradigm shift from a traditional product orientation to the provision of bundled solutions. Particularly the possibility to gather and analyze data has been recognized as a key enabler for the advancement of the product-services offering. In this view, the research presented a systematic literature review exploring the state of the art considering on one side the newest technologies related to data and digitalization and on the other side servitization, aiming at understanding the point of contact between them. Four different perspectives have been identified and discussed and possible research directions have been proposed.

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Unsupervised Crowd-Assisted Learning Enabling Location-Aware Facilities

Cited by 39 publications

References 37 publications

A Survey on Fusion-Based Indoor Positioning

A Survey on Fusion-Based Indoor Positioning

Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

Industry 4.0 Data-Related Technologies and Servitization: A Systematic Literature Review

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