Evidence map›Paper›PMID 38509934›Full record

ArticleHeliyon2024

Advancing sanitary surveillance: Innovating a live-feed sewer monitoring framework for effective water level and chamber cover detections.

Yelbek Utepov, Alexandr Neftissov, Timoth Mkilima, Zhanbolat Shakhmov, Sungat Akhazhanov, Alizhan Kazkeyev, Assel Toleubekovna Mukhamejanova, Aigul Kenzhebekkyzy Kozhas

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Yelbek UtepovDepartment of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.
Alexandr NeftissovResearch and Innovation Center "Industry 4.0", Astana IT University, Astana, Kazakhstan.
Timoth MkilimaThe University of Dodoma, P. O. Box 259, Dodoma, Tanzania.
Zhanbolat ShakhmovDepartment of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.
Sungat AkhazhanovFaculty of Mathematics and Information Technology, Karaganda Buketov University, Karaganda, Kazakhstan.
Alizhan KazkeyevDepartment of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.
Assel Toleubekovna MukhamejanovaDepartment of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.
Aigul Kenzhebekkyzy KozhasDepartment of Technology of Industrial and Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.
L. N. Gumilyov Eurasian National University · KZAstana Medical University · KZKaraganda Buketov University · KZThe University of Dodoma · TZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient sanitation system management relies on vigilant sewage surveillance to uphold environmental hygiene. The absence of robust monitoring infrastructure jeopardizes unimpeded conduit flow, leading to floods and contamination. The accumulation of harmful gases in sewer chambers, coupled with tampered lids, compounds sewer network challenges, resulting in structural damage, disruptions, and safety risks from accidents and gas inhalation. Notably, even vehicular transit is vulnerable, facing collisions due to inadequately secured manholes. The core objective of this research was to deconstruct and synthesize a prototype blueprint for a live-feed sewer monitoring framework (LSMF). This involves creating a data gathering nexus (DGN) and empirically assessing diverse wireless sensing implements (WSI) for precision. Simultaneously, a geographic information matrix (GIM) was developed with algorithms to detect sewer surges, blockages, and missing manhole covers. Three scrutinized sensors-the LiDar TF-Luna, laser TOF400 VL53L1X, and ultrasonic JSN-SR04T-were evaluated for their ability to measure water levels in sewer vaults. The results showed that the TF-Luna LiDar sensor performed favorably within the 1.0-5.0 m range, with a standard deviation of 0.44-1.15. The TOF400 laser sensor ranked second, with a more variable standard deviation of up to 104 as obstacle distance increased. In contrast, the JSN-SR04T ultrasonic sensor exhibited lower standard deviation but lacked consistency, maintaining readings of 0.22-0.23 m within the 2.0-5.0 m span. The insights from this study provide valuable guidance for sustainable solutions to sewer surveillance challenges. Moreover, employing a logarithmic function, TF-Luna Benewake exhibited reliability at approximately 84.5%, while TOF400 VL53L1X adopted an exponential equation, boasting reliability approaching approximately 89.6%. With this navigational tool, TF-Luna Benewake maintained accuracy within ±10 cm for distances ranging from 8 to 10 m, showcasing its exceptional performance.

Indexed as

Geographic information systemInternet of thingsSensorsSewer chamberSewer monitoring

Identifiers

PMID38509934
PMCPMC10950577
OpenAlexW4392648979

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.