Special Issue "Empowering Future Generation of Water Industry through Microbiological Sensors"
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".
Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 185
Special Issue Editors

Interests: sensor networks

Interests: disease recognition using artificial intelligence methods
Special Issues, Collections and Topics in MDPI journals

Interests: metaheuristic techniques; deep learning; artificial intelligence; big data analytics; cyber-physical systems; 5G networks; healthcare big data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The world population has grown over the last two decades due to medical advances that have reduced the average mortality rate while increasing the birth rate of humans. Increased population places a strain on food, water, and air resources. Modern technology offers alternate answers to every challenge without sacrificing quality. Water is one of the most abundant natural resources. However, it is not in a consumable state. Many governmental and private groups invest vast sums of money to inrifying ocean saltwater, which has its own set of drawbacks. As a result, it is critical to efficiently manage water supplies using cutting-edge technology and microbiological sensors.
Microbial sensors are the analytic devices that use the transducers that can biologically integrate with the microorganisms and generate the signal that corresponds to the concentration of microbes. The water industry highly prefers those sensors to provide better water quality services to their customers. These industries provide drinking water and manage water for residential, commercial and industrial sectors. The water industries provide drinking water services to their customers who require a constant monitoring system to maintain the water quality. It is difficult to manually monitor such a huge water resource and provide consistency in services. The water industry employs various enzyme-based sensors, tissue-based sensors, Immuno, and piezoelectric sensors capable of identifying the microbial substances and other living cells in the water resources. All living organisms, including microbes, can produce adenosine triphosphate. The enzyme-based sensor detects these enzymes in the water resource to measure the concentration of microbes. The microbial sensor has been designed to send the alert data or trigger the alarms if the microbial concentration reaches a certain level. The automatic system implemented in the water industry can activate the purifying system to remove the pathogens and microbes present in the water. It also helps to measure the growth rate of microbes in water resources to find the abnormal growth rate due to any extinct species in water. As the water industries also cover the wastewater, including the sewage system, monitoring both pipelines is needed to ensure there is no leakage between them. Some water industries use these microbial sensors to identify the nature of microbes using various electrochemical-based biosensors to redirect the wastewater to agriculture or irrigation purposes. There are a few challenges associated while implementing this in real-time applications. It is difficult to identify the faulty sensor once it is implemented. Which requires weekly or monthly services to maintain the sensor quality. The sensor should operate at low power to produce a stable output by using the energy from the battery during a power cut. To screen a larger area, many sensors are required, increasing the maintenance cost. Most of the sensors are designed to identify specific microbes or microbes with different size ranges, which is considered sensor limitations.
This editorial investigates the use of microbiological sensors to empower the water sector for the next generation and the future advantages and present limits. This motivates sensor designers and water industrialists to delve deeply into the existing constraints and submit research papers to solve them.
Related Topics:
- Rice grain yield prediction on a pilot scale using UAV-based remote sensing techniques pictures.
- VR and AR-based enhancing knowledge of microbial sensors and their applications.
- Designing of Automatic decision-making sensors on real-time data for water quality management.
- Implementation of Microbial sensor for water quality monitoring and its applications.
- Applications of ML based microbial sensors for food processing industries and its futuristic benefits.
- AI based microbial sensor for the measurement of microbial concentration and quality management.
- Design of electrochemical sensors and 2D materials for agriculture industry: Vision, research activist, challenges and solutions.
- Implementation of ultra high adsorption capacity using carbon nanotube for water purification.
- AI-enabled storage systems in the modern power grid: Potential and Constraints.
- New frontiers of carbon nanotube-based biosensor and its industrial applications.
- Application of 1D material based chemical sensors for microbes identification and water quality enhancement.
- Microbial sensor-based data mining and mathematical analysis of growth rate of microbes and preventing water contamination.
Dr. Dilbag Singh
Prof. Dr. Robertas Damaševičius
Dr. Vijay Kumar
Guest Editors
Manuscript Submission Information
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