Science Explorer Interactive view Map

Water Quality Monitoring Technologies

Water Quality Monitoring Technologies is a research topic within Water Science and Technology. Science Explorer counts 44k research works in it since 1950. 11.3% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on real-time monitoring of water quality, aquaculture management, and environmental sensing using advanced technologies such as sensor networks, IoT, and computer vision. The research covers topics including smart sensors, wireless monitoring, fish behavior analysis, and remote sensing for environmental monitoring.

  • Water Quality Monitoring
  • Aquaculture
  • Sensor Networks
  • IoT
  • Computer Vision
  • Fish Behavior Analysis
  • Smart Sensors
  • Wireless Monitoring
  • Remote Sensing
  • Environmental Monitoring
Research works
44k
fractional, since 1950
In the world top 10%
5k
per year above
Top-10% rate
11.3%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+72%
the tick is no change

Which countries lead Water Quality Monitoring Technologies research?

By volume, China and India publish the most (2.9k and 2.3k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.9k works
  2. 2 India 2.3k works
  3. 3 Indonesia 1.7k works
  4. 4 United States 801 works
  5. 5 Malaysia 389 works
  6. 6 Brazil 349 works
  7. 7 ?? 268 works
  8. 8 Japan 248 works
  9. 9 Italy 208 works
  10. 10 South Korea 193 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 30.6%India: 25.0%Indonesia: 18.1%United States: 8.6%6 others listed: 17.7%31%largest
China2,868 · 30.6%India2,343 · 25.0%Indonesia1,694 · 18.1%United States801 · 8.6%6 others listed1,654 · 17.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Water Quality Monitoring Technologies research?

By volume in 2022–2025, SRM Institute of Science and Technology publishes the most Water Quality Monitoring Technologies research, followed by Saveetha University and Vellore Institute of Technology University.

Who are the leading researchers in Water Quality Monitoring Technologies?

The most-cited researchers publishing on Water Quality Monitoring Technologies include Mohamed‐Slim Alouini, MengChu Zhou and Marimuthu Palaniswami.

  1. 1 Mohamed‐Slim Alouini Saudi Arabia 5.9k citations
  2. 2 MengChu Zhou United States 4.4k citations
  3. 3 Marimuthu Palaniswami Australia 3.8k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Water Quality Monitoring Technologies research done?

The largest centres of Water Quality Monitoring Technologies research in 2022–2025 are Beijing (China), Chennai (India), Jakarta (Indonesia) and Bandung (Indonesia). Among places with at least 20 works in it, it is an unusually large share of all research in Zhoushan.

Largest cities, 2022–2025

  1. 1 Beijing China 520 works
  2. 2 Chennai India 336 works
  3. 3 Jakarta Indonesia 207 works
  4. 4 Bandung Indonesia 168 works
  5. 5 Shanghai China 162 works
  6. 6 Nanjing China 156 works
  7. 7 Wuhan China 135 works
  8. 8 Surabaya Indonesia 134 works
  9. 9 Coimbatore India 131 works
  10. 10 Hangzhou China 118 works

Where it is the local speciality

  1. ZhoushanCN · 35.4 works14×
← less than its size predictsmore →

Location quotient: how much more of its research is in Water Quality Monitoring Technologies than the world average.

See Water Quality Monitoring Technologies on the map

Where is the best place to study Water Quality Monitoring Technologies?

Among universities, judged by research, Central Institute of Fisheries Education, Vellore Institute of Technology University and Sathyabama Institute of Science and Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 19.04%fractional works in this node (log) →share in the world top 10% →Central Institute of Fisheries Education: 13, 37.8%Vellore Institute of Technology University: 69, 19.7%Sathyabama Institute of Science and Technology: 28, 10.0%Tun Hussein Onn University of Malaysia: 25, 3.4%Kalasalingam Academy of Research and Education: 22, 10.5%Amrita Vishwa Vidyapeetham: 47, 11.4%Sepuluh Nopember Institute of Technology: 47, 1.8%National Institute of Technology Raipur: 12, 34.7%Amity University: 14, 35.7%Daffodil International University: 11, 25.4%Central Institute of…Vellore Institute of…Sathyabama Institute…Tun Hussein Onn Univ…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Central Institute of Fisheries EducationIndia 66.137.8%36.8×13 +219.6%
2 Vellore Institute of Technology UniversityIndia 59.419.7%5.4×69 +623.8%
3 Sathyabama Institute of Science and TechnologyIndia 58.510.0%10.2×28 +1068.3%
4 Tun Hussein Onn University of MalaysiaMalaysia 56.93.4%10.7×25 +259.6%
5 Kalasalingam Academy of Research and EducationIndia 56.710.5%11.1×22 +362.5%
6 Amrita Vishwa VidyapeethamIndia 55.111.4%6.8×47 +465.4%
7 Sepuluh Nopember Institute of TechnologyIndonesia 54.21.8%8.6×47 +320.7%
8 National Institute of Technology RaipurIndia 52.834.7%6.2×12 +331.2%
9 Amity UniversityIndia 51.935.7%4.0×14 +560.0%
10 Daffodil International UniversityBangladesh 51.925.4%9.1×11

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Water Quality Monitoring Technologies research growing?

Output in 2018–2022 was 72% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Water Quality Monitoring Technologies.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.