Study and design of a retrofitted smart water meter solution with energy harvesting integration

Pimenta, Nelson; Chaves, Paulo

doi:10.1007/s43926-021-00010-x

Cited by 28 publications

(8 citation statements)

References 27 publications

(57 reference statements)

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“…The characteristic of the EEG signal is influenced by the range of artifacts, but in this way, there is no video domain resolution, only the time domain signal resolution can be obtained, and the resolution of the EEG signal itself is relatively high. Because the frequency domain has strong characteristics, the time domain analysis cannot display the electrical activity of the brain more appropriately [4,5]. Compared with the regular and periodic physiological signals such as electrical and pulse, the EEG signal is more complex and is a non-stationary random signal.…”

Section: Feature Extraction Of Brain Componentsmentioning

confidence: 99%

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Huang

Cao

2021

Neural Comput & Applic

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Due to safety issues when passengers get on and off the subway and spend a lot of time on the subway, this makes subway station signs very important. Moreover, in case of fire and other dangerous situations and emergency evacuation, the guiding signs must be able to guide passengers to leave the station and dangerous areas efficiently and orderly, so as to protect the personal and property safety of passengers. The purpose of this study was to analyze the decision response of subway evacuation signs using the characteristics of the brain components. In this study, subway model is constructed. When you perform simulation using software, you need to fine tune the parameters to get the best simulation effect. A questionnaire survey was made on the components of the subway sign. The results show that the number of people who think that the standard font of the blackboard logo is the most representative of the emergency exit, accounting for 78.2% of the total number of people, taking the image as the first choice accounted for 52.9% of the total number of people, and the green sulfur powder logo as the first choice accounted for 69.8% of the total number. This study makes an important contribution to the research of subway traffic safety problems.

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Section: Feature Extraction Of Brain Componentsmentioning

confidence: 99%

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Huang

Cao

2021

Neural Comput & Applic

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“…Cepstrum analysis originated from a new concept proposed by Healy et al (1963) : the “cepstrum” of the logarithmic spectrum. The purpose of cepstrum analysis of speech signals is to obtain cepstrum characteristic parameters for speech recognition and processing ( Pimenta and Chaves, 2021 ).…”

Section: Results and Analysismentioning

confidence: 99%

Intelligent Aging Home Control Method and System for Internet of Things Emotion Recognition

Zhang

2022

Front. Psychol.

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To solve a series of pension problems caused by aging, based on the emotional recognition of the Internet of Things, the control method and system research of smart homes are proposed. This article makes a detailed analysis and research on the necessity, feasibility, and how to realize speech emotion recognition technology in smart families, introduces the definition and classification of emotion, and puts forward five main emotions to be recognized in speech emotion recognition based on smart family environment. Then, based on this, it analyses the acquisition methods of emotional speech data. On this premise, this article discusses and analyses the related problems of voice data acquisition in smart homes, such as the voice characteristics and acquisition methods, puts forward three rules for voice text design, and determines the relatively suitable hybrid recording acquisition method applied in a smart home environment. At the same time, the design and establishment process of intelligent family emotional speech database is described in detail. The related problems of feature extraction in speech emotion recognition are studied. Starting from the definition of feature extraction, this article expounds on the necessity of feature extraction in the process of recognition and analyses the characteristics of the speech signals. For the specific environment of the smart family, the speech signal required to be processed needs to be close to the auditory characteristics of the human ears, and the speech signal contains enough information. Finally, the Mel frequency cepstrum coefficient (MFCC) is selected as the feature parameter applied in this article, and the extraction process of MFCC is introduced in detail.

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“…In [8], water flow is measured using an induction emitter that detects a metal target on the wheel of a mechanical water meter, calculating volume based on wheel movement. A micro-controller counts wheel revolutions and transmits volume data to a remote server via Narrow Band-Internet of Things (NB-IoT) communication, utilizing a tank oscillator and magnetic field interaction.…”

Section: A Related Workmentioning

confidence: 99%

IoT-Enabled Water Monitoring in Smart Cities With Retrofit and Solar-Based Energy Harvesting

Bawankar,

Kriti,

Chouhan

et al. 2024

IEEE Access

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Monitoring water flow helps to identify leaks and wastage, leading to better management of water resources and conservation of this precious resource. To address this challenge, there is a need for an efficient and sustainable water management system. This paper presents an Internet of Things (IoT) based solution that involves retrofitting existing analog water meters using readily available off-the-shelf electronic components. Real-time data collection and analysis are performed through edge computation, which locally processes water meter images captured by the camera and extracts water meter readings. These readings are transmitted to the cloud for storage and further analysis. Various strategies have been implemented to optimize supply-current usage, preserving charge-discharge cycles of solar-powered batteries even in adverse environmental conditions. To streamline the firmware update process for multiple connected devices, a broadcasting technique is employed, offering the benefits of reduced manual labor and time savings. To assess the reliability and performance of developed solution, field deployment is conducted over several months, enabling the characterization of water usage patterns across different locations. Integrating energy harvesting capabilities into system reduces maintenance costs and promotes eco-friendly energy practices. Overall, this solution offers an effective and comprehensive approach towards achieving efficient and sustainable water management.

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Study and design of a retrofitted smart water meter solution with energy harvesting integration

Cited by 28 publications

References 27 publications

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Intelligent Aging Home Control Method and System for Internet of Things Emotion Recognition

IoT-Enabled Water Monitoring in Smart Cities With Retrofit and Solar-Based Energy Harvesting

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