Indoor environmental data collection, localization and fusion

Huang, Chieh-Hsun; Lin, Cheng-Hsin; Shih, Shih-Yu; Chang, Po-Yen; Lin, Yuan-Chi; Huang, Cheng-Ming

doi:10.1109/icce-china.2017.7991030

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Acanthamoebae spp. are known to grow more rapidly at higher temperatures (Jones et al 1992;Rao and Khan 2000;Huang et al 2017). The time at which the highest number of positive samples was observed varied markedly between the two cultivation temperatures, being 6 days for T2 and 8 days for T1.…”

Section: Discussionmentioning

confidence: 99%

The Microscopic Detection and Identification of Acanthamoeba Spp. In Water Samples Following Enrichment by in Vitro-Cultivation Under Two Distinct Temperature Conditions.

Elmahdi

Mostafa

Horia

et al. 2021

Preprint

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Acanthamoeba is a genus of free-living amoeba commonly found in environmental sources such as water, soil and air, and can infect humans. There is a significant challenge in the detection and identification of members of this genus in water samples. In order attempt to overcome this challenge, we investigated using in vitro culture, under distinct temperature conditions, to grow and enrich amoeba prior to detection and identification. Aliquots of 150 water samples, collected from Rabat (30 from each river, fountain, sea, public bath and tap water), were individually inoculated into standard culture medium non-nutritive agar and incubated for two weeks at 25 °C and 30 °C under otherwise standard conditions. PCR was used to confirm the presence of Acanthamoeba DNA in positive samples. The findings showed that Acanthamoeba grew more rapidly at 30 °C than 25 °C, allowing improved microscopic detection and identification at the former temperature. This investigation shows clearly that the diagnostic sensitivity of an in vitro based culture system is temperature-dependent.

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Section: Discussionmentioning

confidence: 99%

The Microscopic Detection and Identification of Acanthamoeba Spp. In Water Samples Following Enrichment by in Vitro-Cultivation Under Two Distinct Temperature Conditions.

Elmahdi

Mostafa

Horia

et al. 2021

Preprint

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An Accuracy Generalization Benchmark for Wireless Indoor Localization based on IMU Sensor Data

Eyobu

Poulose

Han

2018

2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

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A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

Morar

Moldoveanu

Mocanu

et al. 2020

Sensors

112

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Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage (use of known environment data), sensing devices, type of detected elements, and localization method. It groups 70 of the most recent and relevant image based indoor localization methods according to the proposed classification and discusses their advantages and drawbacks. It highlights localization methods that also offer orientation information, as this is required by an increasing number of applications of indoor localization (e.g., augmented reality).

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Indoor environmental data collection, localization and fusion

Cited by 3 publications

References 9 publications

The Microscopic Detection and Identification of Acanthamoeba Spp. In Water Samples Following Enrichment by in Vitro-Cultivation Under Two Distinct Temperature Conditions.

The Microscopic Detection and Identification of Acanthamoeba Spp. In Water Samples Following Enrichment by in Vitro-Cultivation Under Two Distinct Temperature Conditions.

An Accuracy Generalization Benchmark for Wireless Indoor Localization based on IMU Sensor Data

A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

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