Low-cost Color Sensor for Automating Analytical Chemistry Processes

Malkurthi, Shreya; Yellakonda, Kirthi Vignan Reddy; Tiwari, Anushka; Hussain, Aftab M.

doi:10.1109/sensors47087.2021.9639569

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…When the soil's humidity level reaches the maximum specified limit, the water pump will immediately switch off [11]. While the LDR is used to measure the intensity of light [48], When the intensity of light decreases, the LDR's resistance increases, and it will transmit the signal to the controller to turn ON the light. When the light intensity increases, the light will turn off automatically.…”

Section: Control System Of Indoor Plantation Systemmentioning

confidence: 99%

Smart Indoor Plantation System Using Soil Moisture Sensor and Light Dependent Resistor Sensor

Abu

Bukhari

Firdaus

et al. 2022

IJRCS

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Plantation methods, including hydroponics, have been extensively used in agriculture. They also employed a time-based irrigation system for the plant. The goal of this project was to create a self-sustaining indoor plantation system that uses soil moisture sensor data to control the flow of water when the sensor detects that the soil is almost dry. Soil conditions are monitored, and crops are irrigated more efficiently with the help of this new technology. Water is conserved by just watering the plants when they absolutely need it, rather than watering them continually all the time as the traditional method would require. Light-dependent resistors are used to measure the brightness of the surroundings in this project. As a result, the grow light will be activated when the ambient light level drops. With the help of a soil moisture sensor and a light-dependent resistor (LDR), one can create a system that automatically waters and lights plants. Finally, the soil moisture sensor collects data for the sprinkler system and displays it on the LCD screen, and then the appropriate measures are taken. When the soil's humidity level is high, the water that flows will be stopped.

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Section: Control System Of Indoor Plantation Systemmentioning

confidence: 99%

Smart Indoor Plantation System Using Soil Moisture Sensor and Light Dependent Resistor Sensor

Abu

Bukhari

Firdaus

et al. 2022

IJRCS

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“…They also pointed out that the light spectrum will affect the colorimetric results and, so, a comparison of the absorbance spectrum of the colored substance against possible LED emitting spectra is essential to determine the linear relationship between concentration and the analytical signal(s). Numerous publications have evaluated the capability of RGB sensors for colorimetric determination ( [21][22][23][24]). All of these studies have used a light-emitting diode (LED) and an RGB sensor connected to a single-board Arduino for data acquisition and manipulation, which achieved satisfactory results.…”

Section: Introductionmentioning

confidence: 99%

Design of a RGB-Arduino Device for Monitoring Copper Recovery from PCBs

et al. 2023

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The mobile phone industry, one of the fastest advancing sectors in production over the last few decades, has been associated with a high e-waste generation rate. Simultaneously, a high demand for the production of new electronic equipment has led to the scarcity of certain metals. In this context, many recent studies have focused on recovering certain metals from e-waste through the use of bioprocesses. Such recovery processes are based on the action of microorganisms that produce Fe(III) as an oxidant, in order to leach the copper contained in printed circuit boards. During the oxidation-reduction reaction between Fe(III) and metallic Cu, the color of the solution evolves from an initial reddish color, due to Fe(III), to a bluish-green color, due to the oxidized Cu. In this work, a hardware-software prototype is developed, through which the concentrations of the key analytes—Fe(III) and Cu(II)—can be determined in real time by monitoring the color of the solution. This is achieved through the use of a non-invasive system, taking into account the aggressiveness of the solutions used for the bioprocessing of electronic components. In the work presented herein, the evolution of the solution color during the bioprocessing of two different types of waste (i.e., electric cable and mobile phones) is analyzed and then compared with the results obtained for pure metallic copper. The results are validated through comparison of the predicted results with the outcomes of conventional procedures, including offline sampling and analysis of Cu(II) and Fe(III) through atomic absorption and UV-VIS spectroscopy, respectively. The developed monitoring system allows an algorithm to be designed that can fit the evolution of analyte concentrations without the need for sampling or the use of complex, tedious, and expensive analytic techniques. It is also worth noting that the monitoring system is not in direct contact with the solution (which is highly aggressive for the processing of electronic equipment), making the system more durable than classic sensors that must be submerged in the solution. The real-time nature of the obtained information allows for the development of control actions and for corrective measures to be taken without affecting the biomass involved in the process.

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