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DENSO Expands Vision Sensor Detection Angle for Subaru Legacy Outback, Crosstrek Models

KARIYA, JAPAN, Sep 27, 2022 - (JCN Newswire via SEAPRWire.com) - DENSO Corporation today announced it has expanded the detection angle of its vision sensor, increasing the sensor's ability to recognize pedestrians and bicycles around a vehicle to improve road safety. The vision sensor is used on some grades of the SUBARU Legacy Outback, announced on April 13, 2022, for the North American market, and the all-new SUBARU Crosstrek(1), unveiled on September 15, 2022, for Japanese market.Vision sensorMany traffic accidents occur when bicyclists and pedestrians suddenly enter roadways from the side. In Japan, such accidents account for about 30% of all traffic accidents involving pedestrians and about 70% of traffic accidents involving children under the age of 12.(2) Drivers are likely to overlook small children and fast bicycles entering the road suddenly from the side, and even if they notice them, struggle to react in time and accidents may occur. Recognizing the importance of the issue, the new car assessment program in Europe (Euro-NCAP) has made it necessary for new vehicles to be able to detect pedestrians and bicyclists from the side of roadways.DENSO decided to tackle this issue and succeeded in expanding the detection angle of its vision sensor to 128 degrees(3). This has made it possible to detect bicycles crossing the road when driving at low speed and meets the assessment conditions(4) stipulated by Euro-NCAP. Thus, the sensor will help to prevent accidents at intersections and other areas where vehicles, motorcycles, bicyclists and pedestrians come and go at various speeds.A wider detection angle can detect many more objects, which means non-hazardous objects are also detected. This makes it critical for the sensor to decipher which is a threat and which is not. For example, when the sensor detects a bicyclist about to cross the road, if the cyclist brakes and stops, the vehicle can keep driving without a collision. However, if the autonomous emergency braking is activated, the vehicle behavior is unpleasant for the driver and is likely to cause other hazards due to its unexpected behavior. The advantages of a wider angle and practical usage have been achieved by detecting objects well in advance with AI technology, determining whether such objects actually pose a risk based on time-series estimation, and minimizing unnecessary vehicle behavior.DENSO remains committed to developing safety products that are satisfactory to users with the aim of spreading safety features to all vehicles.Below is the image comparing this product with a typical product (detection angle of 100 degrees). By expanding the detection angle to 128 degrees, it is possible to detect crossing bicycles more quickly.(1) The all-new Subaru Crosstrek will be officially announced in autumn, 2022(2) Source: Number of traffic accidents by violation/age bracket of pedestrians (whose negligence is serious compared other parties involved in accidents) in "2019 Traffic Statistics" published by the Institute for Traffic Accident Research and Data Analysis(3) The detection angle of vision sensor is based on DENSO's measurement.(4) Assessment conditions for hazard detection in a situation where a bicycle crosses a road at 20 km/h when one's own vehicle is cruising at 10 km/h. The conditions are considered to be difficult to meet in terms of the angle of view; they have been met by expanding the detection angle.References:SUBURU 2023 Outback for North Americawww.subaru.co.jp/news-en/2022_04_13_163459/All-New Subaru Crosstrek for Japanwww.subaru.co.jp/news-en/2022_09_15_174049/ Copyright 2022 JCN Newswire. All rights reserved. (via SEAPRWire)

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Fujitsu and Southern Tohoku General Hospital start joint research on AI technology for detecting pancreatic cancer from non-contrast CT scans

TOKYO, Apr 25, 2022 - (JCN Newswire via SEAPRWire.com) - Fujitsu and the Southern Tohoku General Hospital today announced the launch of a joint research project with Fujitsu Japan Limited (hereinafter Fujitsu Japan)(1) and FCOM CORPORATION (hereinafter FCOM)(2) on an AI technology for the early detection of pancreatic cancer from computed tomography (CT) scans without contrast agent (non-contrast CT scans) starting April 1, 2022.Figure 1: Detection of suspected pancreatic cancer using the newly developed technologyThe new AI technology has been trained with data from 300 anonymized CT images of pancreatic cancer patients provided by the Southern Tohoku General Hospital and offers an optimal image analysis method based on the shape of organs and cancer tumors. The joint research project represents a new approach to apply AI technology to support medical practitioners in detecting early signs of pancreatic cancer from CT scans.Fujitsu and the Southern Tohoku General Hospital will conduct clinical trials within this joint research to further improve the newly developed AI and offer a technology for an early detection of pancreatic cancer that can help to improve the quality of life of each patient.BackgroundThe 5-year relative survival rate for people diagnosed with pancreatic cancer is 11%(3) which is lower in comparison to other cancer types, as it is the fastest growing type of all cancers and generally difficult to detect. As the pancreas is located in the deepest part of the human body, affected people often don't easily notice any symptoms and thus often don't undergo voluntary medical examination until the cancer progresses. The fact that the entire pancreas is hard to visualize using simple imaging tests such as abdominal ultrasonography and that affected body parts are difficult to identify makes early detection of pancreatic cancer even more difficult.Researchers anticipate that the development of technology capable of detecting microscopic signs of cancer from imaging data and improving test capabilities will play an important role in the early detection of pancreatic cancer.The goal of this joint research is to successfully develop an AI technology that is able to detect signs of pancreatic cancer not only from contrast-enhanced CT scans (scans using contrast agents to make organs more visible) but also from non-contrast CT scans (scans not using contrast agents) to ultimately support the early diagnosis of affected patients regardless of symptoms of pancreatic cancer.Outline of the joint researchThe precise and early detection of signs of pancreatic cancer in non-contrast CT scans represents a difficult task due to the low contrast of images and the unclear boundaries between the pancreas and other organs. To address this issue, Fujitsu and Southern Tohoku General Hospital aim to develop an AI technology that can identify the region corresponding to the pancreas (part marked yellow in figure 1) and detect the suspected parts affected by cancer (part marked red in figure 1). The technology achieves this by estimating the continuity between the anterior and posterior cross-sectional images in consideration of the anatomical tissue connection and automatically performs three-dimensional analysis including the anterior and posterior cross-sectional images in areas with strong continuity and planar analysis in areas with weak continuity.The partners will also apply the newly developed technology in clinical practice to locate typical signs of early pancreatic cancer, including tumors and pancreatic duct dilatation that are often difficult to detect, as well as for findings that require clinical follow-up including cysts and local atrophy of the pancreas.Future PlansMoving forward, Southern Tohoku General Hospital and Fujitsu will continue collaboration with Fujitsu Japan and FCOM toward the realization of an AI technology for the early detection of pancreatic cancer that contributes to a higher quality of life (QOL) for affected patients. The parties will conduct further clinical verification tests as part of their joint research program with the aim to provide an improved AI technology for practical application in fiscal year 2022. Fujitsu further aims to contribute to the creation of a healthy society by applying the results of this research to a wide range of medical and health promotion services as part of its vision for "Healthy Living" under its global business brand FUJITSU Uvance.Comment from Dr. Daizo Fukushima, Southern Tohoku General Hospital"Previous studies at our hospital have shown that non-contrast CT scans can help to diagnose pancreatic cancer at an early stage(4). I am confident that the new AI technology can help to save many patients' lives if it is able to easily identify patients with an increased risk of pancreatic cancer."Comment from Daiki Masumoto, Fellow, SVP, Head of Converging Technologies Laboratories, Fujitsu Research, Fujitsu Limited"We are very pleased to announce the launch of this joint research project through FCOM, which has long supported the medical system of the Southern Tohoku General Hospital. Fujitsu will continue research and development on converging technologies(5) that combine AI-powered image analysis technology with Southern Tohoku General Hospital's medical knowledge in pancreatic cancer treatment, with the aim of establishing AI technology able to support the early detection of pancreatic cancer."(1) Fujitsu Japan Co., Ltd.:Head Office: Minato-ku, Tokyo; President and CEO: Takayuki Sunada(2) FCOM CORPORATION:Head Office: Koriyama City, Fukushima Prefecture; President and Representative Director: Masahiro Saito(3) Survival rate for people diagnosed with pancreatic cancer is 11%:The Japanese National Cancer Center counted and published the actual 5-year relative survival rate for people diagnosed with pancreatic cancer after diagnosis at designated hospitals all over Japan. bit.ly/3MrIHDB (in Japanese)(4) Non-contrast CT scans can help to diagnose pancreatic cancer at an early stage:Journal of Medical Science: Daizo Fukushima, et al., "Characteristic Radiological Features of Retrospective Diagnosed Pancreatic Cancers", Pancreas, Volume 49, Number 1, January 2020. https://pubmed.ncbi.nlm.nih.gov/31856082/(5) Converging technologies:Advanced technologies that combine computer sciences and knowledge from the humanities and social sciences, aiming to solve diverse and complex issues.About FujitsuFujitsu is the leading Japanese information and communication technology (ICT) company offering a full range of technology products, solutions and services. Approximately 126,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$34 billion) for the fiscal year ended March 31, 2021. For more information, please see www.fujitsu.com.About Southern Tohoku General HospitalSouthern TOHOKU General Hospital, was opened in Koriyama, Fukushima. Since 1981, it has developed as the cutting-edge medical facility with the high skill of proton therapy and Boron Neutron Capture Therapy (BNCT). We strive to become a medical hub center in Asia and the world. Press ContactsSouthern Tohoku General Hospital7-115 Yatsuyamada, Koriyama, Fukushima 963-8563, JapanFAX: +81-24-934-5527E-mail: pr@mt.strins.or.jp Copyright 2022 JCN Newswire. All rights reserved. (via SEAPRWire)

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NEC Provides a Predictive Anomaly Detection System Using AI at Suntory’s Natural Water Beer Plant in Kyoto

TOKYO, Feb 18, 2022 - (JCN Newswire via SEAPRWire.com) - NEC Corporation (TSE: 6701) announced today that it will provide Suntory Beer, Inc. with NEC Advanced Analytics-Invariant Analysis, an AI-based facility anomaly detection system. This system is planned to begin operation in late May at the can filling line at Suntory's Natural Water Beer Plant in Kyoto, Japan. The project is being promoted in collaboration with Suntory System Technology Co., Ltd., which is responsible for the Suntory Group's IT technologies, and activities are being conducted with an eye to expanding the project to each Suntory Group company.System Configuration OverviewFilling machineTraditionally, at production lines at manufacturing sites where mass production is undertaken, field personnel mainly use sensor data from equipment to monitor usage thresholds. However, there is a need for experience and know-how in order to understand the fine changes in individual data, and passing these skills along is a challenge.This new anomaly detection system is centered on NEC Advanced Analytics-Invariant Analysis, which uses Invariant Analysis Technology, part of NEC's leading-edge AI technology group, NEC the WISE. By collecting and analyzing a large amount of time-series data from a large number of sensors installed in facilities through control systems such as PLCs (Programmable Logic Controller), modeling invariant relationships between sensors (invariants) and comparing changes between predicted data with actual data, users can detect "irregular" occurrences at an early stage. This system takes advantage of the features of White Box AI and provides information necessary for taking action at maintenance sites, such as where and why functions are performing abnormally. When modeling, users can easily visualize conditions by simply entering the sensor information they want to see with the time that those sensors were operating.A new can filling line using IoT will be started in April at Suntory's Natural Water Beer Plant in Kyoto in order to accelerate DX in production lines. In this line, NEC's system will automatically discover the relationships between approximately 1,500 sensors, and issue alarms when changes occur, thereby detecting equipment anomalies at an early stage and helping to resolve them as soon as possible.Moreover, NEC will install microphones near filling machines in order to analyze when sounds are different from usual, which could possibly indicate an abnormality with the system.In the future, it is expected that these advancements could help to reduce the number of people required for maintenance work, while helping to detect abnormalities more quickly."Through the provision of this system, NEC is supporting the stable operation of facilities, preserving expert know-how and experience, recognizing errors that are difficult to detect, and contributing to the DX of production lines," said Masayuki Ikeda, General Manager, AI Analytics Division, NEC Corporation.About NEC CorporationNEC Corporation has established itself as a leader in the integration of IT and network technologies while promoting the brand statement of "Orchestrating a brighter world." NEC enables businesses and communities to adapt to rapid changes taking place in both society and the market as it provides for the social values of safety, security, fairness and efficiency to promote a more sustainable world where everyone has the chance to reach their full potential. For more information, visit NEC at https://www.nec.com. Copyright 2022 JCN Newswire. All rights reserved. (via SEAPRWire)

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NEC Develops High-speed and High-precision Object Detection Acceleration Technology for Edge Equipment

TOKYO, Dec 1, 2021 - (JCN Newswire via SEAPRWire.com) - NEC Corporation (TSE: 6701) today announced the development of a "gradual deep learning-based object detection technology" that enables efficient and high throughput object detection for video analytics while maintaining detection accuracy.This technology enables up to eight times the processing speed of object detection for large volumes of images, even on edge devices with limited processing capacity.NEC aims to commercialize this technology in fiscal 2022, following further research and development.Video analytics are expected to be utilized for a wide range of applications, such as analyzing camera images of vehicles at intersections, optimizing traffic control, and analyzing camera images of stores and warehouses to detect intrusion or to optimize facility management.To perform these video analytics in real time, it is ideal to process them on an edge device near a sensor, such as a camera.However, because cooling is difficult to manage and electricity consumption is restricted in edge devices, high-performance processors such as GPUs used in high-performance servers are not available, and processing capacity is constrained.In video analytics, object detection software that utilizes deep learning (hereinafter "object detection AI model") performs object detection processing in order to find the object to be analyzed from images captured by a cameraSince highly accurate object detection AI models have a large amount of operations though, it is difficult for edge devices to process a large amount of images due to constraints on processing capacity. If the amount of operations for a high-speed object detection AI model is reduced, for example, the accuracy declines and the recognition accuracy requirements for image analysis cannot be met.Application of NEC's newly developed gradual deep learning-based object detection technology enables efficient, high-speed, and high-precision detection of subjects from a large amount of images, even in an edge device with limited processing capacity, and enables simultaneous processing of images from multiple cameras in real time.Technology Features1. High-speed, high-precision detection at the same timeThis technology combines an object detection AI model that is high-speed, but is only roughly accurate, with another object detection AI model that is highly accurate, but computationally complex. This combination enables efficient processing of multiple images and results in high-speed, high-precision detection.First, a high-speed object detection AI model detects multiple objects quickly, but with rough accuracy, then the detected results are processed together with a high-precision object detection AI model to gradually refine the detected objects.As a result, in an example of detecting a car license plate from a camera image, processing speed was approximately eight times faster than when using an object detection AI model with high accuracy alone, while maintaining detection accuracy*.2. Compatible with various detection targets, detection methods, and AI chipsThis technology is compatible with a diverse range of object detection processes according to detection targets, such as people, vehicles and car license plates, without being limited to specific detection targets and specific processing methods.In addition, the technology's application is not limited to a specific AI chip. By taking advantage of the fact that AI chips have a large number of computing resources in common, the technology makes effective use of the internal computing power of chips.Going forward, NEC aims to enhance the safety, security, and convenience of society by expanding the use of video analytics technologies to a wide variety of applications.*Speed varies depending on the device used, the type of detection engine and the quality of image data.About NEC CorporationNEC Corporation has established itself as a leader in the integration of IT and network technologies while promoting the brand statement of "Orchestrating a brighter world." NEC enables businesses and communities to adapt to rapid changes taking place in both society and the market as it provides for the social values of safety, security, fairness and efficiency to promote a more sustainable world where everyone has the chance to reach their full potential. For more information, visit NEC at https://www.nec.com. Copyright 2021 JCN Newswire. All rights reserved. (via SEAPRWire)

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Universities and DENSO Develop Biosensor to Detect SARS-CoV-2 and Accelerate Development for Practical Application

TOKYO, Oct 21, 2021 - (JCN Newswire via SEAPRWire.com) - Tokai University, Toyohashi University of Technology, Chubu University, and DENSO Corporation have been developing testing equipment to detect SARS-CoV-2 with support from the Japan Agency for Medical Research and Development (AMED)(1). Universities and DENSO announced today that the group has succeeded in developing a biosensor based on a new mechanism and detecting SARS-CoV-2. The group will accelerate the development toward practical application to contribute to early diagnosis of infectious diseases, which is a key factor in limiting virus' spread. To prevent the medical system from being overwhelmed due to viral infectious diseases, it is essential to prevent the spread of viruses by early diagnosis and isolation. At present, PCR tests(2) and antigen tests(3) are used for the diagnosis of SARS-CoV-2. However, these tests cannot evaluate "virus infectivity," which indicates the power of the detected virus to infect. PCR tests are characterized by its high virus detection sensitivity, but effort of sample pretreatment process imposes a high workload on medical professionals. Meanwhile, antigen tests are simple, but the detection accuracy varies. There has been growing demand for a high-sensitivity and simple detection method to evaluate viral infectiousness.The universities and DENSO have been developing a biosensor for clinical testing equipment to enable high sensitive and quick quantitative detection of viral infectivity. Unlike PCR tests and antigen tests, the biosensor detects the spike protein(4) on the virus surface, which triggers infection, by using a semiconductor sensor and aptamer.(5) The group has succeeded in developing highly sensitive detection of SARS-CoV-2 with high sensitivity by using this technique for the first time in the world.(6)The semiconductor sensor can quantitatively measure the viral load by using electrical signals. Thus, it is expected to be used to determine the status of infection and confirm the efficacy of treatment with high accuracy. An aptamer is small in size and binds selectively to various types of protein. It is also easy to design and can be mass-produced quickly, and so the aptamers can be used to detect unknown viruses.The goal of the development of the biosensor by the universities and DENSO is to determine the infectivity of SARS-CoV-2 and offer novel tests which have virus detection sensitivity equivalent to that of PCR tests and which is as simple as antigen tests. The group will enhance the basic technology and accelerate the development toward practical application.The universities and DENSO remain committed to preventing the spread of SARS-CoV-2 infection by harnessing the technologies that have been refined through the project.(1) AMEDUniversities and DENSO develop biosensor with the support of AMED, with the project called "Advanced semiconductor sensor-based biomolecule detection system towards diagnosis of infectious SARS-CoV-2"(2) PCR testA test for detecting genes in a virus.(3) Antigen testIn a typical antigen test, the nucleocapsid protein in a virus is detected using an antibody.(4) Spike proteinProtein on the virus surface. It has the function of binding to human cell receptors and triggers infection. (5) AptamerAn artificially synthesized nucleic acid molecule. It bonds with specific substances.(6) For the first time in the worldWorld's first technology to detect the spike protein by using a semiconductor sensor and aptamer.Respective roles and commentsTokai UniversityFrom the viewpoint of infection control and laboratory physicians, we are eager to develop a system characterized by superb sensitivity and specificity and capable of quick diagnosis to determine infectiousness with simple operation. We offer advice on practical application and ensure accuracy management by using products, which are developed with world-leading engineering capabilities.Toyohashi University of TechnologyWe fabricated a semiconductor sensor capable of converting the viral load into electrical signals and supplied it to this project. The use of semiconductor technology makes it possible to distinguish viruses which cause very similar symptoms in a single test by using a sensor as small as a grain of rice.Chubu UniversityWe prepared and supplied various types of viruses to evaluate the specificity of the semiconductor sensor. This biosensor is capable of quick detection of "infectious viruses" which cannot be determined by conventional methods such as PCR tests. Determination of the status of viral proliferation (that is, whether the viruses that have entered the body keep their infectivity or not) will clarify the timing when viral detection and/or isolation could be finished, and help infected individuals return to normal life.DENSO CorporationWe supplied biotechnology to detect viruses using a semiconductor sensor with higher sensitivity by taking full advantage of our expertise derived from R&D on detecting various viruses and biomarkers, which was conducted as part of advanced research to create a comfortable cabin space. We will accelerate the development toward practical application by leveraging biotechnology and semiconductor technology that have been refined through many years of operations. Copyright 2021 JCN Newswire. All rights reserved. (via SEAPRWire)

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DETAK by Brawijaya University Researchers detects Heart Disease Early and Accurately

Malang, East Java, Indonesia, Nov 27, 2020 - (ACN Newswire) - Researchers from the Brawijaya University (UB) Medical School in Malang, East Java have developed DETAK, a smartphone application for patients with heart disease. The app works on an AI (artificial intelligence) algorithm, to provide early and accurate detection of heart disease, or acute coronary syndrome, and prevent delays in proper diagnose and treatment.Acute coronary syndrome describes a host of conditions linked to the sudden, reduced flow of blood to the heart. One such condition is a myocardial infarction, or heart attack, in which cell death results and can lead to damaged or destroyed heart tissue. DETAK was designed to prevent these types of occurrences with early discovery."Apart from functioning as an early detection tool encouraging patients to seek treatment, DETAK serves to remind heart disease patients to take their medication and undergo medical checkups regularly," noted Mohammad Saifur Rohman, the lead researcher of cardiovascular study at the UB Medical School. The application also offers informative articles on heart disease and advice for maintaining a healthy heart.Rohman drew attention to the importance of the early detection service in the application, since delay in the detection of heart disease is a main causal factors in the high number of heart attack cases resulting in death, citing data from the Dr. Saiful Anwar Hospital in Malang. He attributed this delay in detection mostly to a lack of knowledge and awareness of the symptoms of acute coronary syndrome.For early detection of the ailment, patients using the DETAK app answer several questions related to chest pain they experience and will be notified on where to go to seek help. The app will direct users with high risk of acute coronary syndrome to hospitals with cardiologists on duty, while those with low risk of acute coronary syndrome will be directed to visit nearby health facilities with general practitioners on duty.The DETAK application has already received the Indonesian Museum of Records (MURI) award, and will soon cover health facilities across Indonesia, with data collection in collaboration with the Indonesian Cardiologist Association (PERKI), Indonesian Medical Association (IDI) and other related facilities.For further information, contact:Universitas Brawijaya (UB) Public Relationswww.ub.ac.id and www.prasetya.ub.ac.id. Copyright 2020 ACN Newswire. All rights reserved. www.acnnewswire.com

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Smartphone sensors, fist-sized balls part of PUB’s upgraded toolkit to find underground pipe leaks

SINGAPORE - When Mr Ong Guan started working as a PUB technician in 1976, he made for an odd sight, with a device that looks like a stethoscope in his ears, the other end connected to two metal discs on the ground. This was par for the course at the time, as the equipment he was using - known as geophones - was necessary to pinpoint the position of leaks in underground water pipes. Trained technicians would first press a metal stick with a disc on one end, called a listening stick, against the ground to listen for faint noises generated by water escaping from the pressurised pipes. If they heard an abnormal noise, they would then put on the geophones and slowly walk along the length of ground above the pipes, trying to listen for where the sound was loudest. But the equipment would also pick up noises such as those of passing cars and ambient sounds. So technicians would have to stand still and try to tune out the other sounds in their head, focusing only on the faint noise of underground water. "Sometimes my boss would tell me, can you go and (check the pipes) at 2am, because it would be too noisy before then," said Mr Ong last Friday (Nov 6). Now an engineer at PUB, the 66-year-old recalled that this was an extremely tedious and time-consuming process that relied on a lot of trial and error, and took a lot of manpower. And while some may think that water leaks are a rare occurrence here, PUB has recorded about five leaks per 100km of pipes yearly in recent years. As Singapore's pipe network stretches over about 5,700km, this makes for about 285 leaks a year, or about five a week. Mr Waseem Khan, 31, who leads PUB's Leak Detection Unit, clarified that this is actually one of the lowest rates in the world. The senior engineer added that it is not possible for there to be no leaks in a water system. "As your pipeline ages, it undergoes wear and tear. (Also), with the soil condition you might have corrosion. You might have works ongoing, so third party damage might occur when someone excavates and hits your pipe. So it's not physically possible to achieve zero leaks," he said. PUB said it is important to continually detect and repair leaks - even the small ones - before they escalate, in order to conserve precious water. Thankfully, technology today is very different. A network of 120 sensors line the large water mains here, monitoring and analysing noises in the pipes to pick up the presence of leaks. These sensors are able to accurately identify and pinpoint the location of a leak within 3m. In the three years since the sensors were piloted in 2017, they were able to detect 13 leaks - including a 13mm hole at the base of a pipe beside a major expressway. Following the successful trial, the water agency aims to deploy about 1,200 sensors islandwide before the end of next year.  A SmartBall, a round sensor put into pipes to detect cracks or anomalies along pipe walls via noise signatures. ST PHOTO: KUA CHEE SIONG PUB has also started exploring the use of a SmartBall - a round sensor encased in a protective foam covering. It is put into a pipe and propelled along by the flow of the water. This allows it to detect any cracks or anomalies along the walls of the pipe by picking up noise signatures related to leaks, and survey long stretches of pipe in a single deployment. Over 500km of pipes will be monitored by these sensors over the next five years, said the agency. Finally, PUB's leak detection teams have been equipped with smartphone sensors since last year - the high-tech versions of the listening sticks of the past. One end of the sensor is attached to any smartphone, while the other is placed on a pipe fitting to pick up sounds from the pipe. A smartphone app will automatically digitalise and analyse the sounds picked up by the sensor to help pinpoint the location of leaks. ST PHOTO: KUA CHEE SIONG An app on the phone will automatically digitalise and analyse the sounds picked up by the sensor, while filtering out any ambient noise, accurately pinpointing the location of any leaks. These complement the noise loggers and correlators, devices introduced in the 2000s which also help to check for leaks. Listening sticks are also still used to corroborate the results of the new tools. Demonstrating some of the new technologies on Friday, Mr Ong said that things have improved greatly since the 1970s. "Now with the (technology), we're able to analyse more accurately... you just need to key in something, and it'll tell you where the next (leak) spot is," he said. Using technology has also reduced training time for new technicians, said Mr Khan. "Previously, you'd need a few months, maybe even years, depending on the person, to be able to train them up to use some of these tools for leak detection, whereas now with the implementation of technology, the learning curve has shortened to maybe a few weeks, a few months," he said. Senior engineer Harry Low, 31, uses a listening stick to detect any sound of leaks. ST PHOTO: KUA CHEE SIONG The agency's director of water supply (network), Mr Ridzuan Ismail, said: "PUB is always on the lookout for new technologies for early leak detection, so that we can minimise water loss in the network and increase the resilience of service that we provide to our customers. "With intelligent leak monitoring and detection technology, we are taking a more preventive and predictive approach and moving away from a resource-intensive operation that requires very specialised skills. This will bring us closer to our goal of transforming our operations through digitalisation to becoming a smart utility of the future."

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