Smart City Applications: using a Fog Computing approach

While the majority of Smart City applications can be developed and deployed using traditional approaches, researchers are investigating how a new class of large scale, dynamic applications can leverage the power of Fog Computing, to build and deploy applications that are distributed throughout the smart city running on a variety of devices ranging from city servers, down to embedded computers in traffic signals and light posts.

As part of a longer term research project, Urban Opus has been working with researchers at the University of British Columbia (UBC) to design and build a framework for these class of large scale city wide applications.

Using an extended version of the Node-RED IoT programming language, known as Distributed Node-RED (DNR) application developers can quickly compose their applications using a visual development tool, and then apply constraints to the components to direct where in the city they should run

Once the application is deployed, it is automatically distributed to processing nodes throughout the city – the details of the breaking the application into pieces, their distribution, and making sure they continue to communicate, even when they are relocated, is handled by the underlying DNR platform.

Using this approach – smart city applications can be quickly developed and deployed into the city infrastructure allowing a new class of large scale, dynamic city applications.

Full details are available in this technical paper

Giang, Nam Ky, Rodger Lea, Michael Blackstock and Victor C. M. Leung. “Fog at the Edge: Experiences Building an Edge Computing Platform.” 2018 IEEE International Conference on Edge Computing (EDGE) (2018): 9-16.

The case for a Smart City Data Brokerage

Central to the mission of several Smart City initiatives, eg Urban Opus and UTA, has been the idea of a citizen centric data brokerage – a means for citizens to take control of their data and manage who uses it and how they use it. A data brokerage works by allowing anybody to make their data available, and then to offer that data to others in a controlled manner.

Data brokerage versus open data

You hear a lot about open-data in the smart city community, data that is made freely available, often by cities or other public organizations, and available for anyone to use. It’s well understood by now that data is a powerful tool in the Smart City arsenal – it allows cities to better understand how they operate, where their inefficiencies lie and to better understand the needs of their citizens. Open data is powerful, but has some limitations, not least because it is mostly infrastructure centric or anonymized in such a way to ensure privacy, but reduce usefulness. Importantly, open data is often ‘low value’ data, data that cities and others are willing to ‘give away’.

Data brokerage is an attempt to solve this problem, it focuses on making data available, but in a controlled manner that allows organizations to manage who uses their data and what they do with. In some cases it also allows them to monetize their data – although that’s not required for a data brokerage to operate.

The key distinction is that organizations are able to make data available and control who can use it. Control is managed through specific licensing which in turn offers an ability to control how data is being used. A base level case would be similar to open data hubs, data is made available, anybody can use it and they simply need to acknowledge that the data is made available under one of the many free and open data licenses, e.g. Open Gov or Creative Commons

However, the power of the data brokerage model is that the data could also be licensed, for a fee, with a specific license that allows a single use. Obviously this is the other end of the spectrum from a freely available open source data set – but it serves to show the range of options that a data brokerage offers.

What about citizen data?

The true power of a data broker becomes clear when we consider the case of citizen data. In todays world citizen data is freely harvested by data companies such as Equifax, Datalogix and Exactis, or is gathered in exchange for free services such as google or facebook. However citizens have no control over the data, its usage and in many cases are not even aware that their personal data is being used by third parties. The data broker offers a means to change this situation. How?

By empowering citizens with a means for them to take back control of their data, to control who can access it, and to give them the freedom to rescind access if they wish to.

Data brokerage allows citizens to register, and validate their identity, and then to upload personal data. This could be basic data they provide themselves, or data they take from 3rd parties. For example, Google now allows users to download their own data sets of all data that google holds on them. Imagine the power if users could take this data, and rather than Google deciding who can use it, they can decide themselves – and monetize it if they want to.

Data brokerage is a new idea, and still requires significant work. But its a powerful tool to both unlock valuable data, and give citizens more control over their personal data. Urban Opus is working hard to push these ideas forward. If you want to help, contact us!

Data Brokerage – background reading

Copenhagen’s experiences with data brokerage

Using blockchains to secure and manage data – databroker DOA

Smart City Data Brokerage: lessons from Copenhagen

A city data brokerage is the next step for open data and provides a means for individuals and organisations to publish, buy, sell and trade data. It provides an essential level of trust and control to encourage organizations to make available high value data sets. It also offers a framework in which individuals can begin to share and control access to their personal data.

One of the forefront cities in exploring this concept is Copenhagen, who have deployed a trial data brokerage since 2016. We blogged about the project in 2016 in http://urbanopus.net/smart-city-copenhagen-key-lessons-and-future-directions/

Recently, Copenhagen have published some of their initial finding and lessons learnt in a report that makes interesting reading for those trying to understand how to go beyond the open data model.

Some key facts are:

  1. Data broker built and managed by Hitachi as a PPI type initiative
  2. 140 different datasets available for purchase/use
  3. Over 1000 individuals/organizations involved in the trial
  4. Significant outreach (workshops, hackathons, 1 on 1s) to understand the data landscape

Some key learnings:

  1. data brokerage is still an immature market and needs well developed use cases

Interestingly, the main stumbling block for data sharing is a lack of clear uses cases or exemplars for potential participants. Owners of data are aware that the data has value, and are willing to consider sharing, but they want some clear use cases to help them identify potential buys and help them put a value on the data. Equally, potential data consumers are looking for clear use cases before they commit to buying/using data. A clear lesson, which we already know from the open data movement, is that publishing data in the hope that people will use it, doesn’t really work. Copenhagen heard a clear message that use cases differ significantly for any data set and data needs adapting, augmenting, cleaning in different ways for different users. They offer an interesting example of people movement patterns. While many potential users agree they would like access to such data, what each means by ‘people mobility data’ is very different, eg real time versus historic, granularity of data, geographic spread, data format etc all differ depending on the use case.

  1. Create a data competence hub

This lesson grew out of their experiences working with data providers and consumers. While there was a significant interest in data sharing and brokerage, a significant amount of discussion was needed to engage and work to partner organizations. This was partly because of the immaturity of the market, but also because of trust and liability issues. As such, the project spent considerable time working with potential data users, and matchmaking via individual or group meetings. In a similar fashion, and related to the use case point above, it was clear that data often needed to be adapted or combined before  it became useful to potential users. Again this required discussion around tools and techniques to work with data.

A significant outcome of the project was the realization that a technical data sharing platform, ie the data broker, was a necessary requirement for data sharing, but not sufficient on its own. It needs to augmented by a mechanism or approach that allowed data providers and consumers to engage and negotiate data formats, details and usage. The project has highlighted the notion of data collaboratives – marketplaces where data providers can interact with potential buyers and discuss how to collaborate around data sets. (see http://datacollaboratives.org/)

  1. Create simple guidelines and standards for data publishing

A final lesson was the need to develop guidelines for data publishing, and agree on common formats. This is driven out of the difficulty many potential data users had in accessing and using data. This was partly due to formatting issues with available data – the ubiquitous use of PDF in open-data sets is a common issue – since PDF is a difficult data format to access, tease apart and reuse. However it was also related to the need for toolchains around data that make it simple to access and use the data – for example, a common request was basic visualizations of data to allow potential users to explore data before buying.

Summary

The lessons from 2 years of real data brokerage in Copenhagen are important for any City looking to move beyond the simple provision of open data. Innovation and improved services are possible through better use of data, but it’s not as simple as making the data available and assuming great things will happen. A careful program of technology platform (the data broker) and support via use cases and date community development is also needed.

Smart City technology trends: part 3

Smart Cities: technology trends (Part 3)

Recently I’ve been asked to write a technology trends paper for the IEEE looking at the main technology trends affecting Smart Cities. This is a broad topic, covering a lot of ground and I’ve been forced to pick a subset of technology trends that are affecting the evolution of smart cities. I’ve broken the topic into manageable sections – each a single blog post – as follows:

  • PART 1
    • Smart cities: background and technology ecosystem
    • Key technology areas #1
      • Networking,
      • Cyber-physical systems and the IoT,
      • Cloud and Edge computing
  • PART 2
    • Key technology areas #2
      • Big Data,
      • Open Data,
      • Citizen Engagement
      • Smart City Standards
  • PART 3 (This post)
    • Smart Cities: Impact of technology trends
      • Business issues
      • Recommendations

Smart Cities: An overview of the technology trends driving Smart Cities (Part 3)

Business aspects

Although this trend paper focuses on technological trends, as outlined in the introduction, Smart Cities are complex ecosystems that cut across technological, social, organizational and business domains. Understanding the role-out of technologies and their relative importance in the ecosystem requires an understanding of the business drivers that affect their deployment and uptake and an overview of the Smart City marketplace.

Increased urbanization, the development and growth of newer cities, along with the natural renewal of infrastructure in established cities, means that the Smart City marketplace is both large and growing. While the scope and size of the market is difficult to accurately quantify, and estimates vary, all place the size of the market in the $300-700 billion range. For example, a market scoping [1] by the UK’s Department of Trade and Industry, suggests “We estimate the global market for smart city solutions and the additional services required to deploy them to be $408 billion by 2020. Breaking this down by vertical, in transport for example, Pike Research estimates a global market for smart transport solutions based on digital infrastructure to be $4.5 billion by 2018. These solutions are enabling solutions for a wider market of $100 billion by 2018 which includes the physical and digital infrastructure for parking management and guidance, smart ticketing and traffic management. Also included in this $100 billion are the traditional and new services such as heavy engineering, road design and big data analytics which are required as a result of investment in digital smart transport solutions. “

Similarly a report by Frost & Sullivan[2] breaks down the total spend into market segments, identifying Governance & Education, Healthcare and Energy as three of the largest business opportunities.

Trends and recommendations

This report has highlighted a number of technologies whose evolution and deployment is contributing to the growth of Smart Cities. Some high level observations:

  • Focus on point solutions: While many major cities are aware of, and to some extent pursuing smart city strategies, it is clear that at the moment most Smart City deployments are focused on specific infrastructure needs. For example reducing water loss by upgrading ageing pipe infrastructure, or improving transportation efficiency through monitoring. Companies need to focus on these types of projects and look for incremental ways to connect individual systems (silos) to provide aggregate efficiencies and support new services.
  • Instrumentation and actuation from IoT: As sensors/actuators are being replaced in the system, an increasing percentage of city infrastructure is becoming IoT connected. Cities that are recognizing this and putting in place middleware and cloud systems to capture and use this data will see significant advantages over time.
  • Value from analytics: Today few cities gather and analyze city data in a comprehensive way. Some lead examples do exist but most cities are still developing these capabilities. Both government and industry need to adopt big data strategies as part of their core framework, building from a cloud centric perspective solutions that incorporate data analytics as core capabilities. The growth of this area is likely to rapidly increase over the next decade with significant investment by cities in analytic capabilities.
  • Different regions have different needs. It is clear that the needs of a Smart City in India are different than those in Europe – different regions are grappling with different problems and so will need different solutions. However, the underlying technology trends do not differ and so the problem becomes the most appropriate application of a technology to meet a city’s needs. Companies that are able to adopt a flexible approach to delivering solution will reap benefits.
  • Collaboration is critical. Few, if any companies can deliver a full Smart City solution. Therefore companies need to identify their role in the Smart City solution ecosystem and work to develop partnerships that allow them to collectively offer solutions to cities. Major players will be able to use M&A activity to plug capability gaps.
  • Citizen engagement and activism are shaping the thinking of cities. Companies that can tap into this, and can show how their approaches and solution benefit from Citizen Engagement will accrue advantage through differentiation. Cities that develop comprehensive citizen engagement strategies will also benefit from citizens that are franchised as well as the collective wisdom of the community.

Resources

IEEE Smart Cities initiativehttp://smartcities.ieee.org/

There has been a significant activity by IEEE to promote Smart Cities and to engage cities in using technologies to develop new services. Examples are Core Cities of Guadalajara in México, Trento in Italy, Wuxi in China, Casablanca in Morocco , Kansas City in US.
Additionally this initiative organized the first two international Conferences on Smart Cities successfully implemented in Guadalajara México 2015 and Trento Italy 2016, being planned the third edition for Wuxi China in 2017.
IEEE Industry activityhttp://industry.ieee.org

A portal of IEEE resources targeted at industry and practitioners including content on Professional development, standards and emerging technologies and trends.

BSI Smart Citieshttp://www.bsigroup.com/en-GB/smart-cities/

A set of standards focused resources from the British Standards Institute that focus on the Smart City domain.

References

  • [1] https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/249423/bis-13-1217-smart-city-market-opportunties-uk.pdf
  • [2] http://www.egr.msu.edu/~aesc310-web/resources/SmartCities/Smart%20City%20Market%20Report%202.pdf

Smart City technology trends: part 2

Smart Cities: technology trends (Part 2)

Recently I’ve been asked to write a technology trends paper for the IEEE looking at the main technology trends affecting Smart Cities. This is a broad topic, covering a lot of ground and I’ve been forced to pick a subset of technology trends that are affecting the evolution of smart cities. I’ve broken the topic into manageable sections – each a single blog post – as follows:

  • PART 1
    • Smart cities: background and technology ecosystem
    • Key technology areas #1
      • Networking,
      • Cyber-physical systems and the IoT,
      • Cloud and Edge computing
  • PART 2 (this post)
    • Key technology areas #2
      • Big Data,
      • Open Data,
      • Citizen Engagement
      • Smart City Standards
  • PART 3
    • Smart Cities: Impact of technology trends
      • Business issues
      • Recommendations

Smart Cities: An overview of the technology trends driving Smart Cities (Part 2)

Open data

Another significant trend in Smart Cities is the adoption and exploitation of Open Data. Open Data in the context of Smart Cities refers to public policy that requires or encourages public agencies to release data sets and make them freely accessible. Typical examples are city wide crime statistics, city service levels, infrastructure data, etc. Many governments and leading cities now run open data portals, e.g., the UK and Canadian data portals, (data.gov.uk, open.canada.ca) and city portals such as San Francisco (dataSF.org), and London (data.london.gov.uk).

While Open Data is not a technology trend in itself, it leverages a number of the underlying technologies discussed, such as Cloud Computing, IoT, etc. and is a source of big city data. Open Data is driving the use of these technologies as cities develop open data portals and other city stakeholders begin to exploit access to this open data. Equally it needs to address some of the challenges associated with big data including data security and in particular issues of privacy.

The evolution of open data represents a broadening of the information available related to city operations. It’s primary goal is transparency, but a significant subsidiary goal is to make information available to third parties that can be exploited to improve city services and foster innovation around new services. San Francisco in the USA and London in the UK have led efforts to exploit open data with local companies creating mobile applications based on Park data[1], tourism, parking and transportation[2]. Similar approaches are appearing in cities across the world. It is clear that increasingly cities will make available more data as open data. However, what is also likely is that the ecosystem of open data providers and operators will evolve with an cities taking on less of a role as open data operators and an increasing number of 3rd parties taking city data and curating it for both citizen and business needs. An interesting early example of this is the City Data Exchange operated in Copenhagen[3].

Big data and data analytics

Smart Cities, by their very nature, generate significant amounts of data in their daily operations. The trends identified above, e.g. IoT, Open Data are driving cities to collect and make available additional significant amounts of data – some static but increasingly large parts of it are real-time data. This data exhibits the classic characteristics of Big Data – high volume, often real-time (velocity) and extremely heterogeneous in its sources, formats and characteristics (variability).

This big data can, if managed and analyzed well, offer insights and economic value that cities and city stakeholders can use to improve efficiency and lead to innovate new services that improve the lives of citizens.

The evolving technology that captures, manages and analyses this Big Data, leverages technology trends such as cloud computing. Cities are now able to access and use massive compute resources that were too expensive to own and manage only a few years ago. Coupled with technologies like Hadoop/HDFS, Spark, Hive and a plethora of proprietary tools it is now possible for cities to harness big data and analytical tools to improve the city.

For example Boston, USA is using big data to better track city performance against a range of indicators, but also to identify potholes in city streets and to improve the efficiency of garbage collection by switching to a demand driven approach[4]. New York has developed a system (FireCast) that analyses data from 6 city departments to identify buildings with a high fire risk[5]. London uses a wide variety of city data and advanced analytics to map individual neighborhoods to better understand resource allocation and planning which is made available through the Whereabouts service[6]. Singapore tracks real time transportation and runs a demand driven road pricing scheme to optimize road usage across the island[7].

Citizen engagement.

Citizen engagement represents a complementary aspect of Smart Cities and although not strictly a technical consideration, relies on the data gathering and data management discussed in the open data and big data sections. Essentially it aims to harness technology in support of greater engagement with citizens – partly in an attempt to ‘tap into the collective intelligence’ of cities and partly to understand better what citizens do and need in their daily lives. In this context, engagement is not just with citizens, but with the entire ecosystems, city workers, businesses, tourists etc. While it may be obvious that cities need to engage and listen to their citizens, it is surprising how few channels exist for meaningful dialogue between cities and their citizens. To address this, a trend over the last 5 years in leading Smart Cities is the exploitation of technology to engage and communicate with citizens. This has taken a variety of forms including:

  • Phone or web applications to allow citizens to report city issues such as graffiti, accidents, etc. or to directly engage with city services (often referred to as 311 services in N. America). Originating from work in Washington DC, details of activities in cities such as Boston, Helsinki, London can be found on the open311 organization’s website[8].
  • Hackathons and other developer events to engage the technical community with Open data and new service initiatives. Successful examples include the Code for America program[9] and other tech focused routes adopted in Europe[10]
  • Co-design and user centric design processes to engage citizens in the ideation, design and delivery of new services. This citizen centric approach has be tried in a variety of forms in many cities, with early adopters such such as Milton Keynes[11]in the UK or the EU’s citizen city project[12] developing best practices.
  • Crowdsourcing city data from citizens to better understand the activities and actions of the urban population, or to use citizens to help gather data that is otherwise hard to obtain. Examples include crowdsourcing flood information in Jakarta using tweets[13] and using citizen input to create wheelchair accessibility maps in Böblingen in Germany[14].

Engagement, as described above, is actually an initial step towards empowerment. The ultimate goal of citizen engagement is the empowerment of citizens to take on and improve their daily lives through community leadership.

The 6 major trends identified above are critical to the role out of smart cities and will shape the way technology is used to enrich the lives of citizens. Obviously they are not the only factors, other areas such as security, privacy, environmental sustainability and a host of others cut across these technology trends shaping their evolution and deployment. However, these 6 trends are critical and are shaping the future of our cities. In the next section, we explore standards activities that relate to these 6 areas and to the more general smart city landscape.

Standards

Standards are critical to the evolution of Smart Cities helping to smooth the adoption of new technologies and providing a trusted framework for city authorities and practitioners. All of the technological areas outlined above are subject to intense standardization activities with significant ongoing activity in the standards bodies, both international organizations such as ISO, ETSI and the ITU as well as national bodies and of course the IEEE. A useful overview of the main international activities is captured by the UK’s national body in its Smart City Overview document[15].

The figure above, based loosely on the UK’s Standards documents shows standards body activities grouped into three levels, with Strategic focusing on providing guidance to city leadership, Process looking at procuring and managing smart city projects and activities and technical looking at the lower level details of the technologies used for Smart City projects – obviously IEEE standards tend to focus on the lower part of the diagram.

At the strategic level, an important standard is the ISO 37120 Sustainable development of communities — Indicators for city services and quality of life. This standard, part of a suite by ISO’s Technical Committee 268 identifies 100 indicators that cities should track to allow them to benchmark progress. There are a number of cities moving to adopt these standards and efforts to benchmark across cities by the World Council on City Data[16]. The BSI has led some of the early thinking on a strategic approach to Smart Cities and has recently created the Smart City Institute in conjunction with the UK’s Future City Catapult[17].

At the more technical level, the ISO JTC1 committee has produced useful survey documents on Smart City standards activities and is shepherding two technical standards that are still under development, (from the ISO/IEC JTC1 group) but worth tracking are ISO/IEC AWI 30145 Information technology – Smart city ICT reference framework and the associated ISO/IEC AWI 30146 Information technology – Smart city ICT indicators which are both looking at the ICT infrastructure needed for Smart Cities.

The IEEE, recognizing that the IoT is a critical technology trend, has led efforts to create IEEE P2413™, Draft IEEE Standard for an Architectural Framework for the Internet of Things (IoT). IEEE P2413 (http://standards.ieee.org/develop/project/2413.html) is in development to propose an architectural framework supporting cross-domain interaction, system interoperability and functional compatibility and to fuel the growth of the IoT market. Additionally, the ITU has an active standards group (Study Group 20) in the IoT area[18].

The IEEE-SA is known for taking a system-of-systems perspective in standardization. As an example, in the area of Smart Grids, IEEE 2030®, IEEE Guide for Smart Grid Interoperability of Energy Technology and Information Technology Operation with the Electric Power System (EPS), End-Use Applications, and Loads. A more comprehensive list of IEEE standards related to Smart Cities can be found in the “IEEE standards activities for Smart Cities” document[19].

Summary

The final part of this 3 series blog post explores the ramifications of these technology trends on the business landscape for smart cities and concludes with some recommendations for companies working in the Smart City space. Read Part 3 here

References

  • [1] https://www.greenbiz.com/blog/2013/01/16/how-san-francisco-taps-open-data-city-apps
  • [2] http://data.london.gov.uk/case-studies/
  • [3] http://www.vinnova.se/PageFiles/751333230/Copenhagen%20smart%20city%20opl%C3%A6g%20i%20Stockholm2.pdf
  • [4] http://www.economist.com/news/special-report/21695194-better-use-data-could-make-cities-more-efficientand-more-democratic-how-cities-score
  • [5] http://www.govtech.com/public-safety/New-York-City-Fights-Fire-with-Data.html
  • [6] http://whereaboutslondon.org/#/
  • [7] https://www.lta.gov.sg/content/ltaweb/en/roads-and-motoring/managing-traffic-and-congestion/electronic-road-pricing-erp.html
  • [8] http://www.open311.org/
  • [9] https://www.codeforamerica.org/
  • [10] http://www.nesta.org.uk/blog/power-people-how-cities-can-use-digital-technology-engage-and-empower-citizens
  • [11] http://www.mksmart.org/citizens/
  • [12] https://eu-smartcities.eu/content/citizen-city
  • [13] http://www.citymetric.com/horizons/making-smart-cities-work-people-no-1-crowdsourcing-flood-maps-jakarta-1228
  • [14] http://www.citymetric.com/horizons/making-smart-cities-work-people-no-5-b-blingen-s-crowdsourced-accessibility-maps-1519
  • [15] http://www.bsigroup.com/en-GB/smart-cities/Smart-Cities-Standards-and-Publication/PD-8100-smart-cities-overview/
  • [16] http://www.dataforcities.org/wccd/
  • [17] https://www.bsigroup.com/en-GB/smart-cities/The-Cities-Standards-Institution/
  • [18] http://www.itu.int/en/ITU-T/studygroups/2013-2016/20/Pages/default.aspx
  • [19] http://standards.ieee.org/develop/msp/smartcities.pdf

Smart City technology trends: part 1

Smart Cities: technology trends (Part 1)

Recently I’ve been asked to write a technology trends paper for the IEEE looking at the main technology trends affecting Smart Cities. This is a broad topic, covering a lot of ground and I’ve been forced to pick a subset of technology trends that are affecting the evolution of smart cities. I’ve broken the topic into manageable sections – each a single blog post – as follows:

  • PART 1 (this blog)
    • Smart cities: background and technology ecosystem
    • Key technology areas #1
      • Networking,
      • Cyber-physical systems and the IoT,
      • Cloud and Edge computing
  • PART 2
    • Key technology areas #2
      • Big Data,
      • Open Data,
      • Citizen Engagement
      • Smart City Standards
  • PART 3
    • Smart Cities: Impact of technology trends
      • Business issues
      • Recommendations

Smart Cities: An overview of the technology trends driving Smart Cities

Rodger Lea

Background

According to the UN Population fund, in 2014, 54% of the world’s population lived in Urban areas, approximately 3.3bn people. By 2030, roughly 66%, or 5bn people will live in Urban areas[1]. This not only represents a massive challenge in how we build and manage cities, but a significant opportunity to improve the lives of billions of people. Rising to that challenge, engineers worldwide are turning to new technologies such as the Cyber Physical Systems (IoT/M2M), 5G, Big data analytics etc., searching for new approaches and solutions that will improve city transportation, water and waste management, energy usage and a host of other infrastructure issues that underpin the operation of cities and the lifestyle of urban citizens.

There are many definitions for Smart Cities, ranging from those that focus exclusively on the infrastructure to those that focus more on enabling citizens and communities to act smarter. While no one definition suits all cities, a useful definition[2] we use in this series is from the ITU:

“A smart sustainable city is an innovative city that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects”

This definition emphasis that a Smart City is not just a city that leverage new technologies; it is a complex ecosystem made up of many stakeholders including citizens, city authorities, local companies and industry, community groups. Further, it should be stressed that the geographical boundaries of what is called a Smart City may be wider than the city itself, gathering multiple governance bodies and municipalities, to define services at the metropolitan or regional scale.

In this trend report, we focus on technology trends that are shaping how Smart Cities are evolving, however, it is important to ensure that when considering the application of technologies to solve problems, the human and institutional aspects are taken into consideration. In essence a cardinal goal of the Smart City is to create value for its entire ecosystem, whether this value is financial, quality of life, health, education, time, etc. The value created by a Smart City can be assessed using both quantitative and qualitative metrics.

Smart City technological ecosystems

From the technological perspective, the Smart City ecosystem is a complex one, comprising many technology areas. Major players operate in several areas providing solutions that complement (and sometimes overlap) other players. Those companies that are able to do so, are working towards a convergence point where they can provide end-to-end solutions to city technology needs. However, most players lack the scale to achieve this and must work in collaboration with partners from other technology segments. To visualize the technology ecosystem, we can identify five key technology groupings (based loosely on a Frost and Sullivan report[3]) as shown below.

In much the same way that Smart Cities are in fact complex ecosystems comprising a range of stakeholders, developing and deploying new services into smart cities generally requires a holistic approach to technology deployment. Since Smart Cities are built with a number of sub-systems, e.g. transport, health, energy etc., a system of systems (SoS) approach is needed to reason about and address city and citizen needs. While it is the case that some large companies are able to develop and deploy

effective Smart City services by themselves, this is not the norm. Rather, it is often the case that successful Smart City deployment requires a number of companies to work together to combine solutions and technologies ranging from the low level sensors/actuators, effective data communications, data gathering and analysis to domain specific applications such as healthcare, energy, transport etc.

  • [1] http://www.unfpa.org/urbanization
  • [2] http://www.itu.int/en/ITU-T/focusgroups/ssc/Pages/default.aspx
  • [3] http://www.egr.msu.edu/~aesc310-web/resources/SmartCities/Smart%20City%20Market%20Report%202.pdf

Key technology challenges and enablers

Underpinning the growing Smart City market are a number of broad ICT technology trends that enable the key segments such as energy, transportation, urban planning etc., to exploit new technologies to deliver smart solutions to cities and citizens. In the following section we highlight a number of these key technology trends and their impact on Smart Cities.

Networking and communications

Critical to many of the technology trends related to Smart Cities is the underlying communications infrastructure that enables smart cities to connect infrastructure, devices and people, gather data and deliver services to a myriad of end points. The complexity of the Smart City technological and service ecosystems requires an holistic approach to networking as well as communications that offer support for a range of needs, from infrastructure monitoring through to backbones for digital media enterprises, from household security to city-wide transportation monitoring. These diverse needs dictate that any smart city will encompass a range of technologies from low bandwidth, wireless technologies, such as BLE and Zigbee, through to dedicated fibre optics for backbone needs. Some critical technology trends that will affect future Smart City developments include:

Low Power WAN technologies. Fitting a niche in the technological landscape between personal/local area networking technologies, such as BLE, Zigbee, WiFi etc., and licenced cellular networking, such as existing 3/4G, and the evolution to 5G sit technologies such as LoRaWAN and the evolving 802.11ah. These technologies use unlicensed spectrum and focus on low power and low cost. While some argue they are a stop-gap measure before the deployment of 5G networks, they are the subject of much interest, and a number of trials have been carried out by NTT in Japan, SigFox in France and Australia and Comcast in the USA. One major appeal driving city adoption is the ability to offer a city-wide service, for free, at a relatively low capital cost, an approach taken by the non-profit organization ThingsNetwork[1].

3/4G evolution. While there is significant activities around the development of 5G standards, these are not expected to have full deployment until 2020. In the meantime a number of important initiatives are focused on mid-term evolution of existing cellular technologies. The 3GPP consortium is working on several activities including work on CAT-1 (and Cat-0) as well as the upcoming CAT-M1 and the Narrow-Band Long-Term Evolution (NB-LTE). These standards focus on IoT scenarios and include better energy efficiencies, cost reductions and better penetration/density – all critical for IoT situations in Smart Cities.

5G: Next generation networking (5G) is the subject of intense technological (and business) activity with a number of major initiatives underway. 5G aims to address some of the key future needs of smart cities with higher bandwidth, delivery and performance guarantees, adaptability, energy efficiency and real time capabilities. 5G is still an evolving space, with considerable discussion on its long term goals and technologies[2]. This complexity and rapid rate of change in the 5G space makes it difficult to provide more than a brief overview. For a fuller exploration of 5G please see the IEEE Industry Trend paper on 5G published as part of this series.

Irrespective of the evolution of 4G and the eventual transition of 5G, two critical technology trends that address the need combine multiple evolving technologies are Software-defined Networking (SDN) and Network Function Virtualization (NFV). Obviously this complex networking landscape poses a challenge as operators and users grapple with needs that span multiple technologies. One solution to this is the adoption of SDN and NFV technologies that allow network operators to mix and match services using SDN, and to push more intelligence into their networks (edge processing) using NFV[3],[4].

Cyber Physical Systems and the IoT

Cyber Physical Systems and the Internet of things (IoT), defined generally as the connection and virtual representation of physical devices to the internet, is critical to the growth of Smart Cities. While it is the case that many parts of traditional city infrastructure have been monitored for many years (traffic, water, electricity), these were often monitored using proprietary technologies and maintained as individual silos. The IoT is changing that situation radically. City infrastructure – some of which may have been traditionally monitored – is now being connected using open standard protocols (IP, HTTP, etc.) and made accessible through web technologies such as REST. Lower ‘hookup’ costs are allowing the sensing to expand to more parts of the city infrastructure and enabling higher fidelity sensing. A good example is energy management, although traditionally many cities (via public or local utilities) have been able to measure and monitor some city energy usage, increasingly private and commercial buildings are being hooked up via smart meters which in turn enables the adoption of micro-grid technologies.

Importantly, this trend to better sensing (and actuation) is not just about sensing city infrastructure such as roads and sewers. The costs and accessibility of IoT technologies is allowing private companies to instrument public infrastructure themselves. For example, auto manufacturers are increasingly sensing, not only the car itself, but its surroundings, traffic conditions and even providing sensed data in the case of accidents. Civil engineering firms are deploying sensors to monitor stress in structures such as tunnels, bridges or the quality of road surfaces[5]. Equally, citizens are deploying low cost sensors to track air pollution[6], noise levels or just employing their smartphones as mobile sensor platforms.

Obviously this growth in sensing is underpinned by wired and wireless communications, with low power mesh networking and the eventual move to 5G as key technology trends. While the IoT is driving a revolution in the ways we are able to sense and control the world around us, in the Smart City environment there are several technology trends – and issues – that are driving the way we can harness the IoT.

The sheer volume of data that is being generated is driving its own needs both in the platforms needed to capture and store the data, and in the tools and techniques needed to analyze the real time data. We will explore cloud technologies in support of Smart City platforms as well as trends in Big Data technologies in the sections below.

Cloud and Edge computing

Cloud computing has had a significant influence on the development of Smart Cities, affecting both the way cities manage and deliver services, and enabling a broader set of players to enter the Smart City market. Cloud computing – defined generally as the delivery of computing as a service – has offered organizations such as cities ways to reduce costs and increase efficiency. Due to legal and privacy concerns, cities have been reluctant to exploit the full benefits of public cloud services for core services, but many have used private cloud and some have experimented with public/private or hybrid cloud infrastructure[7]Where public cloud has been exploited, it has often been for non-core services or newer services. For example, Barcelona (Spain) has used public cloud infrastructure to deliver identity services and device management for its field-based workforce[8], for data analytics and to improve its CRM systems for managing citizen interactions.

A secondary factor driving the adoption of cloud solutions for Smart Cities is the massive increase in data that is being generated, captured and analyzed by cities as they start to deploy and exploit IoT technologies. New infrastructure sensing, combined with private data sources and citizen data means that cities now have access to a multitude of high-volume real-time data sources. While there are a number of examples of this use of cloud infrastructure in cities, Intelligent Transportation is a lead use-case, for example Taiwan has exploited cloud computing to handle the high data volume from its intelligent transportation systems (ITS)[9].

While cloud computing is an established part of Smart City solutions, an emerging trend is the augmentation of cloud computing with Edge (also known as Fog computing). Edge computing is a term used to describe the deployment and use of processing within and at the edge of the network[10]. This trend leverages the rollout of IoT infrastructure which often includes powerful processing and gateway devices to gather and communicate sensed data. The Edge computing model offers cities ways to manage and monitor distributed infrastructure – for example Intelligent Transportation Systems (ITS) – where processing is often best handled close to infrastructure for performance and timeliness reasons or building management systems focused on energy efficiency[11].

Part 2 of this report focuses on Big Data, Open Data, Citizen engagement and Smart City Standards

  • [1] https://www.thethingsnetwork.org/
  • [2] http://www.gsma.com/network2020/wp-content/uploads/2015/01/Understanding-5G-Perspectives-on-future-technological-advancements-in-mobile.pdf
  • [3] https://www.opennetworking.org/images/stories/downloads/sdn-resources/white-papers/wp-sdn-newnorm.pdf
  • [4] http://www.cio.com/article/2379216/business-analytics/understanding-how-sdn-and-nfv-can-work-together.html
  • [5] http://www-smartinfrastructure.eng.cam.ac.uk/news/future-cities-foresight-thought-piece-robert-mair
  • [6] https://www.fastcoexist.com/3026502/a-grassroots-environmental-sensor-network-so-you-dont-need-the-government-to-say-the-air-is-
  • [7] http://images.newsletters.lighting.philips.com/Web/PhilipsLighting/%7Bddcf75e7-1e51-40e6-9df2-88a2b59a902e%7D_Future-proofing_IT_for_Smart_City_services.pdf
  • [8] https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=1939
  • [9] http://www.intel.com/content/www/us/en/connected-transportation-logistics/taiwan-fetc-improves-traffic-modernizes-taiwans-transportation-industry.html
  • [10] https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf
  • [11] http://blogs.cisco.com/perspectives/iot-from-cloud-to-fog-computing

Smart City Standards: An overview

Making sense of Smart City standardization activities

Update: For a fuller discussion of Smart City technologies, including standards, read Smart City Technology Trends


Last year I was asked to write an article on Smart City standards for the IEEE standards magazine. This blog post was the basis for that article, but also acts as an evolving document as I update it to reflect standards activities.

First step – get some sort of framework to understand where different standards fit

The amount of activity in Smart City standardization is truly overwhelming – this is partly due to the breadth and scope of Smart City activities – from water pipes to people – and partly because it is early in the process and the standards bodies are still trying to understand how best to contribute.

After spending several days drowning in standards, I decided to step back and try and find a way of categorizing the different standards. I came across a useful framework from the UK’s standards body, the British Standards Institute (BSI), which is part of an excellent (and free) report they’ve written on Smart Cities (PD 8100 Smart city overview)

The Framework categorizes standards into 3 main levels, Strategic, Process and Technical

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Levels of Smart City standards (Copyright BSI 2015)

  • Level 1: Strategic: These are smart city standards that aim to provide guidance to city leadership and other bodies on the “process of developing a clear and effective overall smart city strategy”. They include guidance in identifying priorities, how to develop a roadmap for implementation and how to effectively monitor and evaluate progress along the roadmap.
  • Level 2: Process: Standards in this category are focused on procuring and managing smart city projects – in particular those that cross both organizations and sectors. These essentially offer best practices and associated guidelines.
  • Level 3Technical: This level covers the myriad technical specifications that are needed to actually implement Smart City products and services so that they meet the overall objectives

As the BSI state: “Strategic-level standards are of most relevance to city leadership and process-level standards to people in management posts. However, even technical specifications are relevant to people in management posts as they need to know which standards they need to refer to when procuring technical products and services.”

Using the Framework to position and group standards activities

Once we have a usable framework, the process of trying to fit standards into the levels can begin. The BSI folks have made a useful start – highlighting a number of ongoing international activities that they, as the UK’s standards body, collaborate on – and placing them in the framework.

The main international bodies are:

  • ISO: International Organization for Standards . The main global body that national standards bodies work with and with which many of us are familiar with via “ISO certified”
  • CEN/CENELEC/ETSI: In Europe, standards are developed and agreed by the three officially recognized European Standardization Organisations: the European Committee for Standardization (CEN), the European Committee for Electrotechnical Standardization (CENELEC) and the European Telecommunications Standards Institute (ETSI).
  • ITU: ITU is the United Nations specialized agency for information and communication technologies – ICTs
  • IEC: Founded in 1906, the IEC (International Electrotechnical Commission) is the world’s leading organization for the preparation and publication of International Standards for all electrical, electronic and related technologies. These are known collectively as “electrotechnology”.

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Placing major worldwide standards activities in BSI framework (Copyright BSI 2015)

It’s still a fairly daunting set of activities, but at least we now have a sense of where the major international standards groups are focused and we can begin to take a look at some of the more important activities. In the next section, I highlight a few activities that I’ve come across that I think are important and seem to have significant momentum. If you are looking for a more comprehensive list, then in the final section, I’ve listed up all the activities I’ve come across.

Note, most actual standards documents are expensive – unless you are a member of the standards body – so a casual browse isn’t an option. I’ve linked to official documents and summaries below and if I’ve come across a publicly accessible overview, I’ve added that – if you know of better public information, let me know.

If you are working on Smart Cities today – here’s some standards activities you should at least be aware of

STRATEGIC – AIMED AT THE PROCESS OF DEVELOPING A CLEAR AND EFFECTIVE OVERALL SMART CITY STRATEGY
  • ISO 37120 Sustainable development of communities — Indicators for city services and quality of life. This standard, part of a suite by ISO’s Technical Committee 268  identifies 100 indicators that cities should track to allow them to benchmark progress. Actually there are 17 areas, 46 core and 54 supporting indicators that cities either “shall” (core) or “should” (supporting) track and report. The World Council on City Data (WCCD) has been set up by cities to benchmark cities and has certified 17 global cities. Worth taking a look.
  • From the BSI, BS 8904 has a focus on sustainable communities and “provides a framework as recommendations and guidance that assist communities to improve. The recommendations and guidance are intended to be applied by communities of any size, structure and type.”
  • Two draft ISO standards also looking at sustainable communities are ISO 37101: Sustainable development & resilience of communities – Management systems – General principles & requirements  and ISO 37102: Sustainable development & resilience of communities – Vocabulary. An overview of this ongoing work is here
PROCESS – PROCURING AND MANAGING SMART CITY PROJECTS
  • The development by the BIS of a Smart city framework standard (PAS 181) falls into the Process category: “It provides practical, ‘how-to’ advice, reflecting current good practice as identified by a broad range of public, private and voluntary sector practitioners engaged in facilitating UK smart cities”
  • The development of a Data concept model for smart cities (PAS 182). This is probably worth a look at if you are interested in data hubs and data interoperability issues as it bases some of its work on the UK’s HyperCat IoT interoperability standard.
TECHNICAL – IMPLEMENTING SMART CITY PROJECTS
  • Two technical standards that are still under development, (from the ISO/IEC JTC1 group) but worth tracking are ISO/IEC AWI 30145  Information technology – Smart city ICT reference framework and the associated ISO/IEC AWI 30146  Information technology – Smart city ICT indicators which are both looking at the ICT infrastructure needed for Smart Cities. Need a publicly available overview for these. Draft versions of these documents are available here
  • ISO: Report from JTC1 – looking at ICT for smart cities: A 2014 document that lays out the Smart City space from a technical point of view. There’s a useful diagram (fig 4) that highlights the technical areas that ISO, IEC and ITU are working on as well as details of their standards work and of the overall activities of JTC1 – great info but heavy going.
  • IEEE P2413 (http://standards.ieee.org/develop/project/2413.html) is a developing standard from the Institute of Electrical and Electronic Engineers (IEEE) for an architectural framework for the Internet of Things (IoT). The standard is being designed, when completed, to offer a reference model defining relationships among various IoT verticals such as transportation and healthcare (the same verticals that are being transformed in the world’s transition to smart cities) and their common architecture elements.

It’s also worth taking a look at the full set of BSI standards for Smart Cities. Although these are national standards, the UK seems to have developed a comprehensive set of Smart City activities quite early and they appear to be feeding in to ongoing international organizations.

A somewhat more nascent effort by the US National Institute of Standards (NIST) can be found here – this seems to be more of a ‘call to action’ than actual NIST endorsed standards, but worth taking a look at if you are USA based.

A more comprehensive list of the standards activities in the various International groups

Don’t read any further if you are already feeling overwhelmed – but for those who care (or just like this stuff) here’s a more comprehensive list of standards I’ve come across – returning to the BSI framework:

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The BSI Framework for Smart City Standards activities (Copyright BSI 2015)

ISO activities

  • ISO 37120: Sustainable development & resilience of communities – Indicators for city services & quality of life
  • ISO/TR 37150: Smart community infrastructures – Review of existing activities relevant to metrics
  • ISO 37101: Sustainable development & resilience of communities – Management systems – General principles & requirements
  • ISO 37102: Sustainable development & resilience of communities – Vocabulary
  • ISO/TR 37121: Inventory & review of existing indicators on sustainable development & resilience in cities
  • ISO/TS 37151: Smart community infrastructure metrics – General principles & requirements 7.
  • ISO/TR 37152: Smart community infrastructures — Common framework for development & operation
  • A useful slide deck describing activities of ISO JTC1 – Working group on Smart Cities (WG 11) is here

IEC activities

  • IEC/SEG 1: Systems Evaluation Group on Smart Cities – Most of their activities seem to be working group reports, a list that reference ‘Smart Cities’ can be found here

ITU activities

  • ITU-T SG5 FG-SSC: Focus group on smart sustainable cities
    • SSC-0100-Rev 2: Smart Sustainable cities – Analysis of Definitions
    • SSC-0110: Technical Report on Standardization Activities and Gaps for SSC and suggestion to SG5, ITU-T
    • SSC 162: Key performance indicators (KPIs) definitions for smart sustainable cities

CEN-CENELE-ETSI (aka European) activities

Related Standards

While not directly related to Smart Cities, the following technical standards will play a part because they focus on constituent parts of the smart city:

  • General – IEEE has a document that lists up their standards that they think are related to Smart Cities – available here.
  • Security
    • The National Institute of Standards and Technology (NIST) released a preliminary discussion draft of its Framework for Cyber-Physical Systems. The draft has an ambitious goal: to create an integrated framework of standards that will form the blueprint for the creation of a massive interoperable network of cyber-physical systems (CPS), also known as the “Internet of Things.” In 2014, NIST established the cyber-physical systems public working group(CPS PWG)—an open public forum.

Updates

 You may be interested in my article on Technology Trends affecting Smart Cities which includes a discussion of Smart City Standards.

 This blog has been turned into an article for the IEEE standards online Magazine, read it here

A short history of VRML 2.0

History is interesting. There isn’t one history, rather a collection of narratives that present a perspective on events from particular viewpoints. This was brought home to me recently when, as part of a WebGL book I’m co-authoring (see WebGL Programming Guide) I looked back at work I did on VRML2.0 around 1995 and how it has fed into the VRML2.0, X3D, WebGL story. I realized that in various “re-tellings” our contribution at Sony didn’t play as prominent a role as I thought it deserved. I went back to a book we wrote at the time on VRML2.0 and dug out the intro chapter which explained VRML’s evolution from our perspective. VRML2.0 evolved primarily from Sony’s extensions to VRML1.0 which we called E-VRML and our collaborations with Mitra Ardron at Worldmaker and the folks at the San Diego Supercomputing Centre (SDSC). Here’s our story ……

A Nice timeline created by Mitra Ardron who co-authored the VRML 2.0 proposal with Sony and the SDSC before we worked with SGI

Excerpt from Chapter 1 of Java for 3D VRML worlds, by Lea, Matsuda and Miyashita, New Riders Publishing, 1996, ISBN1-56205-689-1

The origins of VRML 2.0: Moving Worlds

Our original foray into the VRML community was based upon the experience we had gained with E-VRML. When people began discussing the next phase of VRML’s development on the VRML mailing list, we proposed, in Aug’95, E-VRML as a basis for VRML2.0.

The approach used in our initial proposal was similar in approach to that being suggested by Mitra, then with Worlds Inc. but soon to set up his own company, WorldMaker. Mitra had several years experience in the area of multi-user shared environments and was a key member of the VRML community and the VRML Architecture Group (VAG).

Our work was a natural match with Mitra’s and, more importantly, his goals for the long-term development of VRML as a basis for CyberSpace. This allowed us to quickly begin working together to understand if we could merge our respective draft proposals. Mitra not only brought his proposal to the table, but also the work of the San Diego Supercomputer Center (SDSC) groups, who shared the same vision for VRML.

Over the subsequent weeks we refined our ideas, and in Oct’95 we had a first draft of a joint paper that was to form the basis of future work. In early Nov’95, a behaviors workshop was held at the SDSC where several groups interested in behaviors presented their ideas. At this meeting, Mitra, SDSC and Sony agreed to formally work on a joint proposal for VRML2.0. By the end of Nov’95, this joint paper had evolved into a joint proposal. In parallel with that work, SGI had also proposed a first draft of a behavior model. This model, although having many things in common with our work, based its execution model not on the notion of events but on a dataflow model. In addition, the SGI proposal didn’t rely on an external scripting language that manipulated the scene through an API, but used an internal language that interacted with the VRML directly. This approach had its roots in existing technology that SGI had already developed in the area of 3D graphics.

It was clear that there was a certain degree of synergy between the SGI work and ours; but it was also clear to us that a dataflow model was completely unsuited for shared multi-user worlds. Since it made good sense, for both ourselves and the VRML community, to try and combine our proposals, we began discussions in Nov’95. After much debate, SGI were convinced that an event-driven model was more practical, and in early Dec’95 it was formally agreed to combine our proposals.

Shortly afterwards, at the VRML’95 conference in San Diego, this proposal was presented as a joint offering and named Moving Worlds. At the technical session and in the demo session, we used our E-VRML multi-user system to explain the basic principles behind the Moving Worlds proposal and to demonstrate what the proposal would allow scene authors to do.

During the subsequent time-consuming and often fractious six weeks, this basic Moving Worlds proposal evolved to being acceptable to all parties. SGI devoted significant resources to the technical writing, and other companies where invited to comment and contribute to the basic final proposal. In early Feb’96 this proposal was presented to the VRML community as Moving Worlds and put forward as a possible contender for VRML2.0.

From Moving Worlds to VRML2.0

The VRML community had requested, via a request for proposals (RFP), technology for the VRML2.0 standard. This RFP was made in Jan’96, the deadline for submission being February 4th. The goals of this RFP was to ensure that the best technology was evaluated, that the process was open to all members of the VRML community, and that the whole community could evaluate all technology and vote on the final choice.

Other contenders for VRML2.0

The VRML2.0 CFP deadline produced a clutch of proposals; all were excellent in their own right and all addressed very complex issues. In addition to the Moving Worlds proposal, the following five others were submitted.

Apple Computer – out of this world

The proposal from Apple Computer was based on their open 3D meta file format (3DMF) which is also used in their QuickDraw 3D technology. Their proposal basically encapsulated VRML1.0 within a 3DMF file. This approach treats VRML1.0 as just another data format that can be found in 3DMF files.

Lastly, the Apple proposal attacks the problem of multi-authored scenes by designating a master script that is responsible for talking to the browser. This script receives information, via a public interface, from other scripts telling it what they want to do. It then uses this information to update the view the user see by interacting with the browser.

To achieve all this, the scripts have access to a high level API that provides them with routines for controlling graphics data, including support for graphic data manipulation, drawing, selection etc.

The German National Research center for Information Technology (GMD) – The Power of Dynamic Worlds

GMD’s proposal was based on their existing work in the area of Computer Supported Cooperative Work (CSCW). They proposed a set of extensions to the VRML1.0 language that supported an event model, behaviors, a set of new nodes and, interestingly, multi-user worlds. Their proposed approach was to extend VRML1.0 with enough built-in support to allow authors to build dynamic scenes without recourse to an external scripting language. It relied on a rich event model that was extended to work in a multi-user environment. In the same way as E-VRML, events were sent between VRML nodes; however, these events caused the execution of behavior nodes, which manipulated the scene directly.

To support multi-user scenes, the GMD model categorized behaviors as autonomous or shared and allowed events to be propagated between browsers which supported the different categorizations.

IBM Japan – reactive virtual environments

IBM’s Japanese research lab proposed a set of extensions to VRML that used a model of reactive behaviors. Motion engines supporting reactive behaviors could be attached to entities in the scene and were used to describe how the entities changed over time. The motion engines supported their own, built-it, simple scripting language, which allowed scene authors to describe how entities change as a result of incoming events. The motion engines supported a notion of callbacks, so that the system could deliver events, much in the same way as event handlers in E-VRML.

Motion engines could be linked together either serially or in parallel to allow complex interrelated animation to take place.

The IBM proposal has a number of similarities with the GMD proposal, in particular its desire to build behaviors into the scene. However, it had no specific support for multi-user scenes.

Microsoft. ActiveVRML

The proposal for Microsoft was named ActiveVRML and was part of the ActiveX strategy from Microsoft. ActiveVRML was an interesting proposal because the language has its roots in the functional programming world. ActiveVRML was really a functional programming language, designed to support several media types as basic data types in the language.

The strength of ActiveVRML came from the power of the functional programming model. To programmers familiar with procedural or object-oriented languages like C or Java, functional languages often seem weird and incomprehensible. However, one significant advantage of a functional language for the manipulation of rich media formats is that it abstracts away from the notion of time. The passage of time is captured in the functions themselves, allowing programmers to ignore time and so not to have to deal with tricky issues such as synchronization. This benefit is useful for a 3D simulation, which is what a 3D VRML world becomes when you add support for behaviors. However, its strength really lies in supporting multimedia such as audio and video.

It is interesting to note, that unlike most of the other proposals, ActiveVRML lives on. It has been renamed and targeted more at multimedia presentations than 3D interactive environments. This makes sense given that the strength of ActiveVRML in the field of time dependent media.

SUN Microsystems – HoloWeb

The HoloWeb proposal from Sun Microsystems grew out of two internal Sun developments: their long-standing interest in 3D graphics and their recently launched WWW language, Java. HoloWeb was three things – a file format, a programming API and a CyberSpace metaphor. The file format of HoloWeb was a departure from VRML1.0. It didn’t offer a selection of high-level 3D primitives, but a simple subset of dots, lines, triangles and text. What’s more, it was by default a highly optimized format based on compression. This had obvious benefits for file transfer in the WWW.

The basic graphics types could be used to build more complicated 3D models and would be manipulated and managed, via the HoloWeb API, by the Java language.

The HoloWeb viewing metaphor was based on the city model. A home page would be a building in the HoloWeb universe. Viewing a page would be like entering that building, surfing the web like walking down a city street. However, the city metaphor allows more structure than possible in today’s WWW. All computer companies, for example, could be located in the same part of the virtual city, allowing surfers to easily locate information. One interesting aspect of the proposal was that Java programs would also be spatially defined and would have their own 3D coordinates in the HoloWeb universe, allowing them to be manipulated like any other 3D entity.

The vote

The vote on the proposals was taken after in-depth discussions within the VRML community via the electronic mailing list. The results of the vote are shown below and represent a clear victory for Moving Worlds.

vote

Figure 1.2 Results of the VRML2.0 proposal vote

There is no question that all of the proposals had something interesting to offer, and all represented significant and original work. The overwhelming choice of the Moving Worlds proposals was probably less to do with its technical merits – which although good, where not significantly better than some of the other proposals – and more because of the process used to develop Moving Worlds.

From the outset, it was a proposal born of existing expertise from Sony, SGI and Mitra, and represented a distillation of all three of the original proposals. Thus it was already well-discussed and criticized. Further, during the drafting stage, it was well publicized within the VRML community and received a significant amount of input and comment. By the time it was proposed as a candidate for VRML2.0, the proposal was therefore already well honed and represented the collective wisdom of many of the key players in the VRML community.

Evolving a proposal into a standard

The hard task of developing Moving Worlds to be an acceptable basis for VRML2.0 was then begun. Continuing the approach taken in the formation of the proposal, this process was carried out in full view, and with significant participation from, the VRML community. However, in contrast to the time before the vote where there were six proposals to divide peoples attention, now, with only one proposal left, the entire community focused on it. This was an immense effort and coordinated by three SGI members, Rikk Carey, Gavin Bell and Chris Marrin. They performed an excellent job of balancing the differing requirements and goals of the VRML community and reaching a fair consensus on contentious issues.

In parallel with this specification effort, we at Sony began the task of building a VRML2.0 browser that would conform to the rapidly evolving specification. During the period from Apr96 to Aug’96 we publicly released five new versions of the browser, each one tracking the evolving standard and culminating in a version, demonstrated at Siggraph, that supported the final specification. Each one of these versions allowed us to perform checks on the paper specification to ensure that it was both possible to implement and useful.

In parallel, a group a Sony Pictures Imageworks developed a set of multi-user shared VRML2.0 worlds that showed off the facilities of VRML2.0 including movies, animation and Java scripting.

At Siggraph, in early Aug.’96, the VRML2.0 specification was published and made available in its final form. The interest in VRML was now significantly higher than at previous events. There were a large number of companies, small and large, all showing VRML related technology. The majority of this was obviously VRML1.0 related but Sony and SGI displayed VRML2.0 versions of their technology, proving the possibility of building the VRML2.0 specification, and taking the first step towards the dream of CyberSpace.

VRML2.0 current status

VRML is evolving, even while you are reading this. The goal of VRML2.0 was to provide an open, extensible system that supported 3D interactive scenes on the WWW. But our sights, and that of others in the community, still rested on the support for shared multi-user spaces. VRML2.0 is sufficiently open and extensible to allow anybody to begin experimentation into the issues of building multi-user spaces. At the time of writing, Sony, along with a handful of other companies and individuals are experimenting to understand best how to do this. The result of that experimentation will result in new proposals in the area of multi-user standards.

As part of our own experimentation, you will find that the VRML2.0 browser that comes with this book, Community Place, is a full multi-user system. It will allow you not only to experiment with VRML2.0, but also shared multi-user scenes. Since the goal of this book is to show you how to use Java to build standard VRML2.0 scenes, we have restricted most of our discussion to standard VRML2.0. However, at the end of the book, we will return to the issue of multi-user worlds and show you both how to build a simple multi-user server of your own, and how to use some of the multi-user features of Community Place.

Round up

This chapter has tried to give an overview of the development of VRML2.0 as seen from our perspective. That perspective is obviously biased, and concentrates on events and motivations that we think are important. It is clear that VRML is many things to many people and will be used in a wide variety of ways in the coming years. For us, and for many others, a principle use of VRML will be as a building block for CyberSpace. Building CyberSpace is a technical challenge, and will not come eaisly. Our goal in the rest of this book is to equip you with enough information to be able to meld the strenths of Java and the flexibility of VRML so that you can begin building interesting, interactive 3D content. In this way, you can become part of the CyberSpace dream.