Telechemistry 2.0: Remote monitoring of fluorescent chemical reactions

Hsu, Chun-Yao; Prabhu, Gurpur Rakesh D.; Urban, Pawel L.

doi:10.1016/j.ohx.2021.e00244

Cited by 3 publications

(5 citation statements)

References 32 publications

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“…A wide variety of sensors interface with computer devices such as microcontrollers, single-board computers, and conventional computers to convert analog signals into digital raw data to process them further. ,, Raw data often contains unwanted noise and irrelevant information. Extraction of significant information from acquired raw data requires the implementation of data processing procedures such as signal amplification, filtering, and noise reduction. , Sensors can be combined with processors, and operated with appropriate algorithms, machine learning, and AI to manipulate and analyze the data in real-time, which is crucial for taking timely decisions based on the acquired data. − Furthermore, some sensor devices are integrated with the Internet of Things to allow remote monitoring, control, and data analysis. − …”

Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

“… 141 − 143 Furthermore, some sensor devices are integrated with the Internet of Things to allow remote monitoring, control, and data analysis. 144 − 146 …”

Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

“…In other representative work, Hsu et al developed a 3D-printed fluorometric probe for monitoring fluorescence chemical reactions. 146 A Wi-Fi-enabled electronic controller has been incorporated to facilitate the real-time transmission of the sensor data to a cloud-based storage platform. This configuration enables extended and remote monitoring of fluorescent chemical reactions conducted within the laboratory setting.…”

Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

“…This data set is subsequently preserved within the flash memory of the microcontroller board featuring Wi-Fi connectivity, thus enabling the transfer of stored data to the cloud infrastructure for remote data monitoring. In other representative work, Hsu et al developed a 3D-printed fluorometric probe for monitoring fluorescence chemical reactions 146. A Wi-Fi-enabled electronic controller has been incorporated to facilitate the real-time transmission of the sensor data to a cloud-based storage platform.…”

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confidence: 99%

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Automation and Computerization of (Bio)sensing Systems

Raju,

Elpa,

Urban

2024

ACS Sens.

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Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

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Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

“… 141 − 143 Furthermore, some sensor devices are integrated with the Internet of Things to allow remote monitoring, control, and data analysis. 144 − 146 …”

Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

Section: Computer Technology In Sensing Systemsmentioning

confidence: 99%

mentioning

confidence: 99%

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Automation and Computerization of (Bio)sensing Systems

Raju,

Elpa,

Urban

2024

ACS Sens.

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“…The Temperature and Humidity Sensor(DHT22) [21] sensor was used to measure temperature and humidity [22] , which is a digital sensor [23] that reads temperature with a variation from −40 °C to 80 °C ± 0.5 °C and air humidity from 0 to 100 % ±2-5 % [24] , as described in Table 3 .…”

Section: Hardware Descriptionmentioning

confidence: 99%