A Shazam-like Household Water Leakage Detection Method

Seyoum, Solomon; Alfonso, Leonardo; Andel, Schalk Jan van; Koole, Wouter; Groenewegen, A; Giesen, Nick van de

doi:10.1016/j.proeng.2017.03.253

Cited by 23 publications

(13 citation statements)

References 6 publications

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“…Hasilnya metode tersebut dapat mengekstrak file komponen mode sinyal kebocoran dari gangguan, sehingga dapat meningkatkan kesalahan posisi kebocoran dibandingkan dengan metode denoising konvensional. Pada [4] menjelaskan tentang A Shazam-like household water leakage detection method, penelitian tersebut untuk mendeteksi kebocoran pada pipa rumah tangga menggunakan rekaman sinyal suara. Hasilnya sinyal suara yang diakibatkan dari kebocoran akan digunakan sebagai acuan bahwa telah terjadi kebocoran air.…”

Section: Pendahuluanunclassified

Rancang Bangun Sistem Proteksi Kebocoran Pada Prototipe Mesin Reverse Osmosis Berbasis Mikrokontroler

Sirait

Aulia

2021

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Penggunaan mesin reverse osmosis untuk memenuhi kebutuhan air layak minum dalam industri food and beverages adalah satu kesatuan yang tidak dapat dipisahkan. Salah satu permasalahan yang sering terjadi adalah kebocoran pada mesin tersebut. Pada penelitian ini dirancang sebuah alat rancang bangun sistem proteksi kebocoran prototipe mesin reverse osmosis berbasis mikrokontroler untuk mengurangi kerugian yang diakibatkan dari kebocoran. Proteksi kebocoran pada sistem menggunakan solenoid valve yang berfungsi mengatur buka atau tutup valve air. Sistem mendapat masukan dari sensor tekanan dan debit, sensor tersebut digunakan untuk menentukan apakah telah terjadi kebocoran. Keluaran yang dihasilkan berupa sinyal yang mengatur buka atau tutup solenoid valve dan mengirim pesan ke whatsapp bahwa telah terjadi kebocoran. Berdasarkan pengujian yang telah dilakukan sistem ini dapat memproteksi kebocoran dengan aktifnya solenoid valve (tutup) saat sistem mendeteksi kebocoran. Selisih debit air masuk dengan debit air keluar lebih dari 1 ml/s dan selisih tekanan air masuk dengan tekanan air keluar lebih dari 10 Kpa, maka sistem akan menganggap telah terjadi kebocoran. Semakin besar lubang kebocoran maka selisih tekanan air dan selisih debit air semakin besar. Sistem dapat mengirim pesan kebocoran ke whatsapp menggunakan komunikasi serial antara arduino mega2560 dengan pycharm IDE.

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Section: Pendahuluanunclassified

Rancang Bangun Sistem Proteksi Kebocoran Pada Prototipe Mesin Reverse Osmosis Berbasis Mikrokontroler

Sirait

Aulia

2021

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“…Other approaches have also been proposed in the technical literature based on other kinds of measurements, such as noise measurements. For example, [18] presented a system to detect leaks in a home environment on the basis of the sound produced by the water in the pipes. The identification of the leaks is made by a "Shazam-like" approach: a sensor records the sounds made by the water network and sends the records to a server which contains a database of sounds.…”

Section: Related Workmentioning

confidence: 99%

Neural Network Techniques for Detecting Intra-Domestic Water Leaks of Different Magnitude

Zese¹,

Bellodi

Luciani

et al. 2021

IEEE Access

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Nowadays, water leak control at different levels is a necessary tool for sustainable water resource management. Research shows that more than one third of the world's drinking water is lost during its transfer to users, and that leakages on users' properties vary between 2 and 13% of total residential water demand, are very frequent and difficult to detect. Thanks to the advances in Internet of Things solutions for smart metering devices, it is possible to gather household water consumption information with high spatial and temporal resolution and to analyse them. This article applies several supervised Machine Learning (ML) techniques for the automatic detection of leakages of different magnitudes -even smaller than the meter sensitivityin pipes within the dwelling, by using data collected by smart meters installed at the connection of users to the distribution network in an Italian town. The results obtained are compared with the performance of an "empirical algorithm" previously presented by the authors, able to automatically identify leakages by checking if the hourly flow rate is never zero during the whole day, but not able to distinguish the size of the leakages. Experimental results over about 40,500 records show that ML techniques significantly improve the detection performance both in discriminating between presence and absence of leakages and in discriminating different-size leakages.

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“…However, the water leakage detection accuracy was not improved. A new household leakage detection approach was introduced in (Seyoum et al 2017) through the sound signal recordings. However, the method was costly and hard to execute.…”

Section: Related Workmentioning

confidence: 99%

Random Bagging Classifier and Shuffled Frog Leaping Based Optimal Sensor Placement for Leakage Detection in WDS

Rayaroth

Gopalakrishnan

2019

Water Resour Manage

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Water Distribution Systems (WDS) are the large scale systems that demand design of enhanced leak detection and isolation techniques to prevent from water waste. Leakages lead to imperative loss of water in water distribution networks. Many works are published on leak detection of WDS. However, the existing methods failed to improve the leakage detection accuracy and reduce the time. In this paper, Random Decision Tree Bagging Classifier based Shuffled Frog Leaping Optimization (RDTBC-SFLO) Technique is introduced. In RDTBC-SFLO, the collected pressure data are taken as training data. Random ID3 decision forest classifier process constructs the ID3 decision tree and produces the classification results of pressure data. After classification, number of nodes at abnormal pressure data is randomly generated as initial population in shuffled frog leaping optimization process. The fitness value of every node is calculated and the optimal nodes are chosen for the sensor placement in WDS with higher accuracy and minimal error rate. The simulation results show that RDTBC-SFLO technique increases the performance of water leakage detection with minimum classification time when compared to state-of-the-art works.

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A Shazam-like Household Water Leakage Detection Method

Cited by 23 publications

References 6 publications

Rancang Bangun Sistem Proteksi Kebocoran Pada Prototipe Mesin Reverse Osmosis Berbasis Mikrokontroler

Rancang Bangun Sistem Proteksi Kebocoran Pada Prototipe Mesin Reverse Osmosis Berbasis Mikrokontroler

Neural Network Techniques for Detecting Intra-Domestic Water Leaks of Different Magnitude

Random Bagging Classifier and Shuffled Frog Leaping Based Optimal Sensor Placement for Leakage Detection in WDS

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