An embedded Electronic Nose for identification of aroma index for different tea aroma chemicals

Das, Amritasu; Ghosh, Tarun Kanti; Ghosh, Arghya; Ray, Hena

doi:10.1109/icsenst.2012.6461745

Cited by 7 publications

(6 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where, C is the gas concentration in ppm, A and α are constants set as 1 × 10 6 and 1 respectively, for the simulation in Fig. 3 [7]. Using (1) and ( 2), (3) can be derived.…”

Section: Performance Evaluation a Accuracy Improvement By Adaptive Re...mentioning

confidence: 99%

“…Chemiresistive sensors have been widely investigated and used for toxic/harmful gas detection [1]- [3], environmental monitoring [4]- [6], food inspection [7]- [10] and various other applications [11] because of their merits such as simple sensing mechanism, cost effectiveness, and excellent sensitivity. The chemiresistor or chemiresistive sensor is a class of chemical sensor that changes its electrical resistance in response to chemical interaction between the sensing material and the target analyte.…”

Section: Introductionmentioning

confidence: 99%

“…A variety of chemiresistive sensing materials, including conductive polymers, nanomaterials such as single and multi-wall carbon nanotubes (CNT), graphene, and nanoparticles can be deposited on the flexible substrate, using Inkjet or screen printing techniques to generate a high density sensor array with wide range [37]- [39]. However, it is hard to achieve fast, accurate, and low power system with the existing E-Nose readout systems; moreover, they are usually expensive and bulky [3], [5]- [7], [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Readout System for High Speed Interface of Wide Range Chemiresistive Sensor Array

Lakshminarayana

Park

et al. 2022

IEEE Access

View full text Add to dashboard Cite

This paper aims at designing a compact readout system for chemiresistive sensor array with high speed and high accuracy. The proposed scheme is based on Resistance-to-Voltage (R-V) conversion and targets high density wide ranged chemiresistive sensor, with input resistance range of 1 K -1 M and 0.1% sensitivity. The proposed approach uses Adaptive Reference Resistor Tuning (ARRT) technique implemented with a digital variable potentiometer to achieve a high accuracy without sacrificing the dynamic range and the speed. The system is implemented on a printed circuit board with a microcontroller and a 16-bit Analog-to-Digital Converter (ADC), and it has a compact dimension of 10 cm × 6 cm, which is suitable for portable applications. The readout system works with a 5 V power supply, and the overall system power consumption is 150 mW. The system is designed to interface with a 118 sensor array and the experimental results achieved a satisfactory accuracy of 0.88%, as well as a measuring speed of 8.5 ms per sensor. Compared with existing approaches, our work targets a high density wide ranged chemiresistive sensor array and demonstrated high accuracy, high speed with the lowest circuit complexity, which is the novelty of this work.

show abstract

“…where, C is the gas concentration in ppm, A and α are constants set as 1 × 10 6 and 1 respectively, for the simulation in Fig. 3 [7]. Using (1) and ( 2), (3) can be derived.…”

Section: Performance Evaluation a Accuracy Improvement By Adaptive Re...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Readout System for High Speed Interface of Wide Range Chemiresistive Sensor Array

Lakshminarayana

Park

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The basic elements of an electronic nose are an odor sensor and an actuator. Proposals to use the electronic nose in detecting optimum tea fermentation have been proposed in References [14,[29][30][31][32]. In Reference [31], a handheld electronic nose is proposed, while in Reference [32], ultra-low power techniques have been incorporated into an electronic nose.…”

Section: Related Workmentioning

confidence: 99%

An Optimum Tea Fermentation Detection Model Based on Deep Convolutional Neural Networks

Kimutai

Ngenzi

Said

et al. 2020

Data

View full text Add to dashboard Cite

Tea is one of the most popular beverages in the world, and its processing involves a number of steps which includes fermentation. Tea fermentation is the most important step in determining the quality of tea. Currently, optimum fermentation of tea is detected by tasters using any of the following methods: monitoring change in color of tea as fermentation progresses and tasting and smelling the tea as fermentation progresses. These manual methods are not accurate. Consequently, they lead to a compromise in the quality of tea. This study proposes a deep learning model dubbed TeaNet based on Convolution Neural Networks (CNN). The input data to TeaNet are images from the tea Fermentation and Labelme datasets. We compared the performance of TeaNet with other standard machine learning techniques: Random Forest (RF), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Naive Bayes (NB). TeaNet was more superior in the classification tasks compared to the other machine learning techniques. However, we will confirm the stability of TeaNet in the classification tasks in our future studies when we deploy it in a tea factory in Kenya. The research also released a tea fermentation dataset that is available for use by the community.

show abstract

“…Some studies have focused on the use of portable e-noses for detection of malodours from animal farms and landfills [ 71 , 72 ], however, mixed results were obtained. For the above-mentioned reasons, a vast majority of hand-held e-noses use an enclosed, static headspace sampling system and are intended for the analysis of food and agricultural products [ 73 , 74 , 75 ], and models in which dynamic sampling of atmospheric air are used are intended for analysis of localised gas leaks and emissions [ 76 ]. Exemplary applications of portable electronic nose instruments for evaluation of air odour quality are shown in Table 3 .…”

Section: Portable Electronic Nose Instrumentsmentioning

confidence: 99%

Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants

Szulczyński

Wasilewski

Wojnowski

et al. 2017

Sensors

View full text Add to dashboard Cite

This review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents commercially available sensors utilized in the electronic noses and characterized by the limit of quantification below 1 ppm v/v, which is close to the odour threshold of some odorants. Additionally, information about bioelectronic noses being a possible alternative to electronic noses and their principle of operation and application potential in the field of air evaluation with respect to detection of the odorants characterized by unpleasant odour was provided.

show abstract

An embedded Electronic Nose for identification of aroma index for different tea aroma chemicals

Cited by 7 publications

References 4 publications

A Readout System for High Speed Interface of Wide Range Chemiresistive Sensor Array

A Readout System for High Speed Interface of Wide Range Chemiresistive Sensor Array

An Optimum Tea Fermentation Detection Model Based on Deep Convolutional Neural Networks

Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants

Contact Info

Product

Resources

About