Review of new developments in different types of sensors over the past 15 years

Ador, Md. Sazzad Hossain; Bhattacharjee, Prattusha; Kabir, Sarower; Ahmed, Md. Tanvir; Ahmed, Fuad; Choudhury, Imtiaz Ahmed

doi:10.1016/b978-0-323-96020-5.00043-1

Cited by 3 publications

(3 citation statements)

References 113 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this way, chemical sensors have attracted greater attention in broad commercial applications such as industrial, environmental, agricultural, and clinical fields. 22,25 Biosensors are sensors or a type of chemical sensor composed of a biological molecule as the recognition component. Therefore, biosensors are classified as analytical devices containing biological or biological-derived sensing components either unified within or closely linked with physicochemical transducers for the recognition of analytes.…”

Section: Biosensorsmentioning

confidence: 99%

See 1 more Smart Citation

Paper-based sustainable biosensors

Kumar,

Maiti

2024

Mater. Adv.

View full text Add to dashboard Cite

show abstract

Section: Biosensorsmentioning

confidence: 99%

“…In this way, chemical sensors have attracted greater attention in broad commercial applications such as industrial, environmental, agricultural, and clinical fields. 22,25…”

Section: Biosensorsmentioning

confidence: 99%

Paper-based sustainable biosensors

Kumar,

Maiti

2024

Mater. Adv.

View full text Add to dashboard Cite

show abstract

“…Optical sensors are used to measure light rays from artificial light sources (such as LEDs, and lasers) and convert the collected data, such as intensity, color, or wavelength, into electrical signals for quantification [206]. Commonly used types of optical sensors include photoresistors, photodiodes, phototransistors, charged-coupled device (CCD) cameras, and complementary metal-oxide semiconductor (CMOS) cameras.…”

Section: ) Optical Sensorsmentioning

confidence: 99%

A Survey of Wireless Soil Sensing Technologies

Xu,

Smirnov,

Kohler

et al. 2024

IEEE Access

View full text Add to dashboard Cite

This survey overviews recent advancements in wireless soil sensing technologies, such as sensors and communication systems to manage and enhance soil health and crop production for sustainable agricultural practices. The surveyed technologies are categorized by the target sensing parameters, such as moisture, temperature, salinity, pH, nutrient concentration, pressure, and heavy metals content. Special focus is placed on the passive and semi-passive sensing principles for soil data collection, communication systems for transmitting the sensed data, and machine learning approaches for data processing and analysis to assist in informed decision-making in the realization of sustainable agriculture. By comparing existing technologies, we highlight the advantages and disadvantages of these sensing mechanisms, summarize existing challenges of the surveyed soil sensing systems, and identify future research directions that need attention.

show abstract

Virtualized Viscosity Sensor for Onboard Energy Management

Gascoin,

Valade

2024

Energies

View full text Add to dashboard Cite

Essential for decision-making, measurement is a cornerstone of various fields including energy management. While direct methods exist for some quantities like length, most physico-chemical properties require indirect assessment based on observable effects. Historically, pressure was measured by the water column height, and temperature by mercury expansion. Recent advancements in artificial intelligence (AI) offer a transformative approach by combining vast datasets with traditional measurements. This holds immense potential for applications facing extreme conditions and involving complex fluids where measurement is extremely challenging (over 1500 K and 5 MPa). In this study, an AI model is evaluated to replace online rheometers (293–1173 K, 0.15–3.5 MPa). A machine learning model utilizes a neural network with up to 8000 neurons, eight hidden layers, and over 448 million parameters. Trained, tested, and validated on three experimental databases with over 600 test conditions, the New Generation Predicted Viscosity Sensor (NGPV sensor) achieves exceptional accuracy (less than 4.8 × 10−7 Pa·s). This virtualized sensor proves highly relevant for hypersonic airbreathing applications involving fuel degradation and energy conversion. It maintains excellent predictability (accuracy below 6 × 10−6 Pa·s) even at flow rates 10 times higher than calibration, surpassing traditional rheometers limited by calibration needs and a lower viscosity measurement threshold (10−4 Pa·s).

show abstract

Review of new developments in different types of sensors over the past 15 years

Cited by 3 publications

References 113 publications

Paper-based sustainable biosensors

Paper-based sustainable biosensors

A Survey of Wireless Soil Sensing Technologies

Virtualized Viscosity Sensor for Onboard Energy Management

Contact Info

Product

Resources

About