September 21, 2021

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New 3D city model of Singapore’s public housing

Image credits: ual.sg/
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The Urban Analytics Lab at the National University of Singapore (NUS) has developed a 3D city model of all public housing (HDB) buildings in Singapore.

It generated the model by combining data from various open datasets. Since most of Singapore’s population reside in public housing, the datasets consist of information of the nation’s residential buildings.

The Urban Analytics Lab mentioned that it is a rising trend across the world for the release of 3D city models as open data. This is to allow researchers and practitioners of different disciplines to use 3D geoinformation to conduct various spatial analyses.

Hence, they too will be releasing this 3D city model of the HDB buildings as open data.

They will be offering the models in two formats: CityJSON and OBJ.

The CityJSON dataset contains information such as the address and number of units in each block. It even goes into detail of stating the number of rooms.

Both formats can be retrieved from their Github repository.  Urban Analytics lab stated that while the dataset consists of significant data and covers almost all buildings, it is still under development.

Procedure

Urban Analytics Lab explained on how it achieved the formation of this model through the process of extrusion. They used information such as the height of each object, which is commonly attained using an airborne laser scanning method or lidar, and the geometry of the footprint. This process allows for the creation of LoD1 (block) models, which the developed 3D city model is currently presented as.

Challenges

The challenge associated with this process is the lack of open data on the heights of objects. In Singapore, there aren’t any publicly available lidar datasets.

Solution

Hence, Urban Analytics Lab used the number of storeys on each block as an estimate for the height of the blocks. Data on the number of storeys in each block has been made available as open data in Singapore. While they acknowledge that this method comes with its inaccuracies, it is largely used across the world and has aided various research work employing such data.

Urban Analytics Lab employed data from sources such as 2D building footprints from OpenStreetMap and HDB Property Information.

Both sources were linked using OneMap’s geocoder.

The dataset consists of information of all types of HDB buildings, which includes commercial building and carparks. Urban Analytics Lab added that there are about 12 thousand HDB buildings in Singapore.

There have been other initiatives which involved the need for use of 3D mapping technology for improving the analysis work of HDB buildings.

In an earlier OpenGov article, we reported on the Building and Construction Authority (BCA) and Housing & Development Board (HDB) having launched a Call for Proposal on using drones for Building Facade Inspection.

BCA and HDB feel that there is an urgent need of a new inspection model, using innovative solutions to improve the inspection efficiency, reduce safety risk to personnel, save time and at the same time being cost-effective.

The current inspecting building facades is a slow, resource and manpower intensive process.

The project is categorised into 2 main phases – Phase 1 comprising of Phase 1A & 1B, and Phase 2 comprising of Phase 2A & 2B.

Phase 1A focuses on the development of drone image mapping & processing software. To aid this process, the software should provide mapping and image indexing for traceability (position, geolocation, date, time of the survey, etc.).

Hence, technology solutions such as the visual 3D reconstruction of building for general building visualization and localisation of defects with the ability to pan, rotate and zoom should be enabled.

The 3D rendered model should be linked to an individual or group of high-resolution images to allow closer examination by inspectors and for allowing the overlay of defects or anomalies on its surfaces.

Mobile Money in Vietnam Paves the Way for New Sandbox Initiatives

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The trial Mobile Money service approved by the Prime Minister will set a precedent for applying a “sandbox” scheme for new services and professions in the digital society. Sandbox is a controlled institutional framework applied to new technologies, products, services, and business models. It is an environment for technology firms to try their new technological apps and business models. After the trial period, management agencies will review the trial implementation and then accept or reject it.

Using laws to set rules to deal with new issues arising from the application of new technologies is a challenge. As per a press release, the apps may have a rapid impact on society that management systems may not be able to keep up with. Many traditional business fields have changed, and businesses have to utilise technology to work more effectively. It is impossible to manage new services and business models within the existing framework because policies tend to lag behind practices. Therefore, a sandbox model is more advantageous.

According to an industry expert, it is impossible to demand state management agencies to create policies for the future. Many countries apply sandbox policies to encourage enterprises to develop new business models, with certain limitations in deployment. The Prime Minister has put into effect the pilot implementation of Mobile Money services – making payments for small-value goods and services with telecom accounts. The pilot programme will last two years.

This is the first service that the government has applied the sandbox mechanism managed by several ministries and branches. The government hopes the service will contribute to the development of non-cash payments, and promote the access and use of financial services, especially in rural areas. Businesses can only provide Mobile Money to remit money and make payments for legal goods and services in Vietnam in accordance with current laws. Mobile Money is only applied to domestic transactions with a monthly transaction value limit of VND10 million (US$4,397).

Vietnam is not the first country that has accepted a new technology platform, but experts said that it has an advantage by learning lessons from predecessors. In Vietnam, the proportion of credit card users is still low, but mobile subscriber density is very high. 99% of transactions with a small value of below VND100,000 (US$4) are carried out in cash. Mobile Money will be a strong solution to promote non-cash payments in society.

The Minister of Information and Communications stated that Mobile Money is a convincing example that shows that telecom carriers can become platforms for many things, not only telecom infrastructure. They can become platforms for data, computing, digital content, authentication, IT services, and the Internet of Things (IoT).

Mobile Money is expected to help Vietnam become a digital society. The project is the first sandbox involving many ministries and sectors to be piloted to meet the needs of society. It will pave the way for more sandboxes to be applied to other new services and business models in the future. He added that Mobile Money is a great opportunity for mobile network operators to build an ecosystem to accelerate digital transformation.

The Philippines to Accelerate National ID Program

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The National Economic and Development Authority (NEDA) said it is accelerating the implementation of the Philippine Identification System (PhilSys) or the national ID programme to enhance the government’s ability to deliver various social services. NEDA chair said that more than 42 million Filipinos had registered as of September for step 1 or collection of demographic data. Notwithstanding the quarantines, he said nearly 30 million took the second step to supply their biometrics in the registration centres.

OpenGov Asia reported that the National Economic and Development Authority (NEDA) expects the Philippine Statistics Authority (PSA) to register 50 to 70 million people for the national digital ID by the end of the year. It is noted that as of July 2, 37.2 million people had completed Step 1, which involves the collection of demographic information, and 16.2 million had completed Step 2, which involves the capture of biometrics at designated registration centres.

The impact of the Covid-19 pandemic is challenging, but the Philippines has a solid foundation to recover at the right time. Reforms such as Rice Tariffication Law and the National ID are helping us restore our development trajectory and enabling the people, especially the poor, to access affordable food and better social services. 

– NEDA Chairperson

Speaking on the progress being made by the digital ID project, Socioeconomic Planning Secretary at NEDA said: “The COVID-19 crisis underscores the need to provide unhampered access to banking and social services for all Filipinos, especially the poor. Therefore, the President gave the directive to accelerate the implementation of the Philippine Identification System or PhilSys to provide all Filipinos with a unique and digitalised ID.”

He underlined that the Filipinos, particularly the poor, would be able to open bank accounts where cash transfers can be received directly. “We aim to register at least 50 million Filipinos by the end of this year,” he said.

The pandemic gave new promptness and highlighted the primacy of financial integration into government crisis containment and rehabilitation efforts. It showed the vital role of financial inclusion in social welfare and protection, as the transaction accounts became a necessary means to receive government cash support from the poorest and most vulnerable in the country.

As per NEDA’s Chairperson, PhilSys would also facilitate financial inclusion by providing every Filipino with a valid proof of identity, which is required for low-income earners to open bank accounts, receive cash transfers, and access other financial services.

Meanwhile, the Philippines’ state-run bank said it has signed up 5.3 million unbanked PhilSys registrants for their own transaction accounts via account opening booths at select PhilSys co-location areas nationwide. The registrants have already used their prepaid cards for a total of P31.8 million in transactions.

The PhilSys registrants can use the Landbank prepaid cards to manage funds, withdraw cash, perform cashless transactions, shop and pay bills online, and receive government subsidies digitally. As per the president and CEO of the Philippines bank, bringing unbanked Filipinos into the financial mainstream lays the groundwork for inclusive growth, particularly as we accelerate initiatives toward economic recovery and sustained development. Access to formal banking services motivates people to save money, repay loans, invest in financial products, and achieve financial independence.

Unbanked PhilSys registrants may access bank transaction accounts after completing the PhilSys Step 2 registration process, which includes validating supporting documents and capturing biometrics data. PhilSys registrants can also activate their bank prepaid cards and conduct transactions through the bank’s mobile branches, which are located in communities across the country where banking services are disrupted or limited.

The bank’s mobile branch is intended to serve unbanked and underserved communities as well as areas affected by disasters, calamities, and other disruptive events, as part of the bank’s increased efforts to promote greater financial inclusion in the community.

CityU Develops Painless Drug Delivery Tech

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A research team led by biomedical engineers at the City University of Hong Kong (CityU) has developed a new generation of microneedle patches made of ice that melt after the pain-free delivery of drugs.

Experiments using this ground-breaking invention on mice with cancers have shown that the animals’ immune responses were much better than those seen in conventional vaccination methods. The technology paves the way for developing an easy-to-use cell therapy and other therapeutics against cancers and other diseases.

Made from a cryogenic solution, these icy microneedles are less than 1mm long and can deliver living mammalian cells into the skin. The device is like a skin patch and the microneedles can detach from the patch base, melt and then penetrate the skin.

The research is led by Dr Xu Chenjie, Associate Professor in the Department of Biomedical Engineering (BME), and the findings were published in Nature Biomedical Engineering under the title “Cryomicroneedles for Transdermal Cell Delivery”.

Dr Xu explained that traditional cell therapy for skin disorders is invasive, painful, complicated, low-efficient, risks infection, and requires experienced professionals. The ready-to-use device can circumvent complex and redundant procedures during each drug administration. In addition, it can be stored for months in a refrigerator and is easily transported and deployed.

The applications for this device are not limited to the delivery of cells. It can package, store, and deliver any type of bioactive therapeutic agents such as proteins, peptides, mRNA, DNA, bacterial, and vaccines, and it can improve both the therapeutic efficacy and patient compliance during cell therapies.

As a proof-of-concept, the researchers explored cell-based cancer immunotherapy through the intradermal delivery of ovalbumin-pulsed dendritic cells. Experiments showed that vaccination using therapeutic cells through this technology elicited robust antigen-specific immune responses and provided strong protection against tumours in mice.

These results were superior to the therapeutic outcomes of conventional vaccination methods. One of the start-up teams supported by the Seed Fund of HK Tech 300, CityU’s flagship innovation and entrepreneurship programme, is working on transferring the technology into a product and to promote its application.

Dr Chang Hao, a former postdoc in CityU’s BME, is the first author of this study, and Dr Xu is the corresponding author. Other researchers include Professor Wang Dongan and Professor Shi Peng from BME. The research team collaborated with scientists from Nanyang Technological University and the National University of Singapore.

The cell therapy technologies market is projected to reach US$5.6 billion by 2025 from US$2.8 billion in 2020, at a CAGR of 14.4% from 2020 to 2025. The emerging economies such as Australia and China are expected to provide a wide range of growth opportunities for players in the market which is driven by their large and growing populations as well as an increase in the number of clinical trials and investments in the field of personalized medicine in these countries.

The outbreak of COVID-19 is expected to have a minimal or negligible negative impact on the cell therapy technologies market. The rise in the incidences of COVID has led to an increase in the need for an efficient drug or vaccine for COVID, which could help in reducing the severity of the cases.

Cell-based research is an essential step during the manufacturing of vaccines, which can help in the growth of the market.

In the initial months of the outbreak of COVID, disruption in the supply chain had been witnessed, which has delayed the clinical trials. This can negatively impact the market to a certain extent. For instance, biopharmaceutical companies and major players have announced clinical trial delays.

AI Predicts Film Genre Based on Soundtrack

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A film is not complete without relevant and good music in the background. Music establishes atmosphere and mood and influences the audience’s emotional reactions as well as their interpretation of the story. A research team at the USC Viterbi School of Engineering sought to objectively examine the effect of music on cinematic genres. Their study aimed to determine if AI-based technology could predict the genre of a film based on the soundtrack alone.

While past work qualitatively indicates that different film genres have their own sets of musical conventions—conventions that make that romance film sound different from that horror movie—Narayanan and team set out to find quantitative evidence that elements of a film’s soundtrack could be used to characterise the film’s genre.

The study was the first to apply deep learning models to the music used in a film to see if a computer could predict the genre of a film based on the soundtrack alone. They found that these models were able to accurately classify a film’s genre using machine learning, supporting the notion that musical features can be powerful indicators in how people perceive different films.

This work could have valuable applications for media companies and creators in understanding how music can enhance other forms of media. It could give production companies and music supervisors a better understanding of how to create and place music in television, movies, advertisements, and documentaries in order to elicit certain emotions in viewers.

In their study, the team examined a dataset of 110 popular films released between 2014 and 2019. They used genre classification listed on the online database of information related to films to label each film as action, comedy, drama, horror, romance, or science-fiction, with many of the films spanning more than one of these genres.

They then applied a deep learning network that extracted the auditory information, like timbre, harmony, melody, rhythm, and tone from the music and score of each film. This network used machine learning to analyse these musical features and proved capable of accurately classifying the genre of each film based on these features alone.

The team also interpreted these models to determine which musical features were most indicative of differences between genres. The models didn’t give specifics as to which types of notes or instruments were associated with each genre, but they were able to establish that tonal and timbral features were most important in predicting the film’s genre.

The researchers examined the auditory information from each film using a technology known as audio fingerprinting. This technology allowed them to look at where the musical cues happen in a film and for how long. Using audio fingerprinting to listen to all of the audio from the film allowed them to overcome a limitation of previous film music studies, which usually just looked at the film’s entire soundtrack album without knowing if or when songs from the album appear in the film.

In the future, the team is interested in taking advantage of this capability to study how music is used in specific moments in a film and how musical cues dictate how the narrative of the film evolves over its course.

AI has been adopted in various areas, including healthcare. As reported by OpenGov Asia, U.S. Scientists have developed a new, automated, AI-based algorithm that can learn to read patient data from Electronic Health Records (EHR). The scientists, in a side-by-side comparison, showed that their method accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labour to develop and perform.

Indian Scientists Develop Data-Processing Technique to Accurately Measure Soot

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Researchers from the Indian Institute of Technology in Bombay (IIT-Bombay) have developed a new data-processing technique to measure low amounts of soot accurately. This will help designers build better combustion-based devices such as internal combustion engines in cars.

Soot is tiny black particles that rise from a flame. Soot is formed when the fuel does not burn entirely. When fuel burns properly, a blue flame is emitted, whereas the flame is yellow when the soot is formed during burning and it becomes hot. Soot can cause cancer and respiratory and cardiac disorders and can also reduce the life of machine parts, a news report has explained.

Accurately measuring small amounts of soot can be a challenge and has spawned several research projects. The team from IIT-Bombay demonstrated a new technique to effectively reduce measurement errors when soot is present in low amounts. They analysed digital camera pictures of burning fuel to guess the temperature of the fuel and use the information to estimate the soot volume. The amount of soot can be measured using methods such as collecting and weighing the soot and studying a light beam shone on soot particles. The current study uses the last method. The researchers passed a beam of red laser light of a specific frequency, through a droplet of burning fuel and took images as it burnt. The light falling on the camera also contains the light from the burning fuel. The researchers used a narrow band filter to let only the laser light pass and filter out the light emitted by the burning fuel.

The report noted that when a flame having soot particles is shone with light, called background light, the particles absorb and scatter some of this light, so light reaching the camera is less bright. The researchers used the relation between the initial brightness of the laser light, the brightness of the light falling on the camera, and the soot volume to calculate the amount of soot. They then used a data-processing technique to compute the values of brightness from their images. Their challenge was to estimate the initial brightness of background light falling on soot particles since this isn’t directly captured in the images.

The team predicted the brightness of background light at every moment instead of using an average. They observed the flickers in background light at areas present outside the flame of the burning fuel, where there is no soot. They used it to estimate the background light falling on the soot particles. Using the new data processing technique, the team got lower errors, especially when the amount of soot produced is low. The technique does not require any additional equipment or extra expenditure, an added advantage.

The report added that to further reduce errors in the experiment, the researchers passed the laser light beam through a fixed and a rotating diffuser — a glass sheet that scatters light — before the light was incident on the burning fuel. A diffuser gives an evenly bright light and avoids the many speckles in the camera image. Speckles need to be removed while processing the data, leading to a loss of information. The researchers also validated their data processing technique. They used it to calculate the amount of soot for some previous measurements reported in the literature and verified the results. They also qualitatively checked their experimental observations.

They burnt a droplet of toluene (a carbon-based fuel) and compared their experimental observations with that in the literature. The team observed a similar peak value of the amount of soot. As expected, they saw high amounts of soot slightly inside the outer edges of the flame, where temperatures and fuel concentration are high, a researcher explained. The quantification of soot is crucial from an environmental perspective. This is an effective method to quantify soot to help identify strategies to mitigate combustion-based practices in India.

Singapore Computer Model to Reduce COVID-19 Infections

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A team of scientists from Nanyang Technological University, Singapore (NTU Singapore) has developed a predictive computer model. When tested on real pandemic data would have reduced the rate of both COVID19 infections and deaths by an average of 72% based on a sample from four countries.

The model, called NSGA-II, could be used to alert local governments in advance on possible surges in COVID-19 infections and mortalities, allowing them time to put forward relevant countermeasures more rapidly.

The main goal of our study is to aid health authorities to make data-driven decisions in fighting the global COVID-19 pandemic. The critical knowledge discovered in historical data enables us to provide early warning, preparation, and prevention for crisis control and enhance the resilience of human societies.

– Assistant Professor NTU’s School of Civil and Environmental Engineering and lead researcher

Through the testing of the model in four Asian countries using data available, the team demonstrated that it could have helped reduce the number of COVID-19 infections and deaths by up to 76% in Japan, 65% in South Korea, 59% per cent in Pakistan and 89 per cent in Nepal.

The computer model achieved the result by recommending timely and country-specific advice on the optimal application and duration of COVID-19 interventions, such as home quarantines, social distancing measures, and personal protective measures that would help to thwart the negative impact of the pandemic.

The team also showed NSGA-II could make predictions on the daily increases of COVID-19 confirmed cases and deaths that were highly accurate, at a confidence level of 95%, compared to the actual cases that took place in the four countries over the past year.

Harnessing the power of machine learning, the research team developed the model by inputting large amounts of data on COVID-19 mortalities and infections worldwide that is available for the whole of 2020, helping it learn the dynamics of the pandemic.

As the pandemic progresses and the COVID-19 virus undergoes many mutations, it threatens the resilience of global society across every aspect of daily life, the environment, and the economy, and it requires the prompt and prioritised attention of policymakers worldwide.

The developed computer programme could serve as a useful tool to help governments formulate strategies and interventions at an early stage to limit or even counter a predicted surge in cases, reducing infections and mortality rates.

The team plans to introduce more variables, such as economic status and cultural differences, into the model to further improve its accuracy. They are seeking to validate its efficacy by including data from additional countries in Europe and North America, providing insights into COVID-19 evolution across different geographies.

As reported by OpenGov Asia, Singapore’s healthcare community have learned various things from the Covid-19 experience that can guide the way they deliver care in the future. Accurate information is essential as the basis for informed decisions. Moreover, people can take more control of their healthcare destinies when they are empowered by information and technology.

As Singapore and much of the world is turning the corner on the pandemic, it is driving the adoption of transformative technologies in healthcare. In the last year, it was the intense and unrelenting pressures of the pandemic that ultimately proved to be the most potent agent of change for digital transformation in healthcare.

The necessary elements of this transformation—the required infrastructure—are rapidly coming to maturity. It starts with the increasing availability of health data from connected devices. It is unleashed by the increasing sophistication of technologies like Artificial Intelligence (AI), hybrid cloud and automation.

Digital Transformation Vital to Vietnam’s Agricultural Development

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To achieve its targets to become a modernity-oriented industrialised nation by 2030 and a developed country with high income by 2045, Vietnam must succeed in the digital transformation process, in which agriculture is one of the priority areas, the Minister of Foreign Affairs stated at the Vietnam Agricultural Digital Transformation International Forum 2021.

The event was co-organised via videoconference by the Ministry of Foreign Affairs, the Vietnam Digital Agriculture Association (VIDA), and an e-newspaper outlet under the theme “Keeping up with market trends, ensuring the pivotal role of the economy during and after the COVID-19 pandemic.” The forum was an activity within the framework of the Vietnam International Agricultural Exhibition 2021 (AgriTech Expo 2021).

According to a news report, the forum consisted of two discussions that focussed on policy orientations and the theme “Shaping Vietnam’s digital agriculture until 2035” with the presentation of 20 speakers representing local authorities and leaders of businesses and corporations. Participants at the event shared scenarios of Vietnam’s agricultural digital transformation; key issues in Vietnam’s agricultural development strategies towards digitalisation given the complicated effects from the COVID-19 pandemic, supply chain disruption, and climate change.

The Minister of Foreign Affairs noted that the Vietnamese government should proactively and actively participate in the fourth industrial revolution and speed up the digital transformation process. The country must consider it a vital solution and an opportunity to make a breakthrough in socio-economic development.

Speaking at the event, the Minister of Agriculture and Rural Development pledged to offer all resources and the most favourable policies for businesses, aiming to bring added value to Vietnamese agricultural products and improve their trademarks. The Ministry will strongly support the digital transformation process and replace agricultural technology models as the Vietnamese agricultural sector is not only the “backbone” of the economy in difficult times but also a measurement of sustainability, the Minister said.

Representatives of foreign diplomatic agencies in Vietnam and from research institutes and socio-economic organisations attended the event. Also, domestic and foreign experts in the field of agricultural digital transformation from Japan, the Netherlands, Israel, and the World Bank as well as those from business associations and enterprises.

In August, the Ministry of Information and Communications (MIC) unveiled a plan to put farming households on e-commerce sites. Farming households will be supported to enter e-commerce sites to connect, advertise, and introduce their products. This will help them access new distribution channels and expand to domestic and international markets. Vietnam has nine million agricultural production households and four million private business households. All the households will be brought onto e-commerce sites, and this will be the first breakthrough to be made in developing the digital agricultural economy.

As OpenGov Asia reported, through e-commerce sites and digital platforms, farming households will receive useful information about farm produce markets, predicted demand and production capacity, weather forecasts, and seed and fertilizer supply. High-quality input materials and tools for agriculture production will be introduced to farmers via the platforms. Overall, MIC will put 12-13 million agricultural production and private business households on e-commerce sites. The targeted figure is five million households by the end of the year.

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