System for facilitating real-time water quality assessment using Internet-of-Things and trained machine learning model for inference, has processor determines portions per million concentration of chemical analytes in sample solution of water by reconstructing RGB color
	MALKURTHI S; GOYAL C; HUSSAIN A M
	2024-01-08
专利权人	INT INST INFORMATION TECHNOLOGY (ITIN-Non-standard)
申请日期	2024-01-08
专利号	IN202441001396-A
成果简介	NOVELTY - The system has an automatic powder dispenser module (202) automatically dispenses a reagent N-diethyl-p-phenylenediamine (DPD) powder to a Poly-Lactic Acid (PLA) sample chamber (210). A sensor module (204) that comprises a Light Emitting Diode sensor (204A) and Light Dependent Resistor pair (LED-LDR) (204B), where the LED sensor is configured to illuminate a sample solution of water within the PLA sample chamber through a transparent acrylic face of the PLA sample chamber. A water quality assessment server that is communicatively connected to the PLA sample chamber. A memory (206) that includes a trained ML (110). A processor (214) that executes the trained ML. The processor determines portions per million concentration of chemical analytes in the sample solution of water by reconstructing the RGB color based on normalized intensity of the reflected RGB light from the sample solution of water using the trained ML to obtain an assessment of water quality. USE - System for facilitating real-time water quality assessment using Internet-of-Things (IoT) and a trained machine learning (ML) model for inference. ADVANTAGE - The system ensures higher accuracy, high reliability and user-friendliness in the measurement process. The system reduces the need for constant water flow to obtain accurate readings, and reduces sensitivity to pH and temperature variations, and allows the system to test for pH as well. The system for minimizing maintenance efforts, and improves overall usability and efficiency. The system significantly reduces the overall time required to obtain results. The system achieves high accuracy for trace chlorine concentrations, and reduces the need for specific sample temperature requirements, and reduces the time required for each measurement to less than 30 seconds. DETAILED DESCRIPTION - An INDEPENDENT CLAIM is included for a method for facilitating real-time water quality assessment using Internet-of-Things and a trained machine learning model for Inference. DESCRIPTION OF DRAWING(S) - The drawing shows a block diagram of a system for facilitating real-time water quality assessment using Internet-of-Things and trained machine learning model for inference. 102User device 110Trained ML 202Automatic powder dispenser module 204Sensor module 204ALight emitting diode sensor 204BLight dependent resistor pair 206Memory 214Processor
IPC 分类号	C02F-001/76 ; G01N-021/31 ; G01N-033/00 ; G06N-020/00 ; G06N-003/08
国家	印度
专业领域	化学化工
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/18538
专题	中国科学院新疆生态与地理研究所
作者单位	INT INST INFORMATION TECHNOLOGY (ITIN-Non-standard)
推荐引用方式 GB/T 7714	MALKURTHI S,GOYAL C,HUSSAIN A M. System for facilitating real-time water quality assessment using Internet-of-Things and trained machine learning model for inference, has processor determines portions per million concentration of chemical analytes in sample solution of water by reconstructing RGB color. IN202441001396-A[P]. 2024.

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