Cities are like Tolstoy's families: each messed up in its own way. The new challenges urban conglomerates have to face and how to better address them were the main topics of discussion at the Smart City in Focus conference which took place in Yinchuan (China) a couple of weeks ago. If for Atlanta, Georgia, transportation and public safety are the top priorities to address, in the struggling desert utopia of Masdar City, the focus is on renewable energy and smart buildings.
As many cities increase in size across multiple dimensions such as population, economic output and physical size, new methods for understanding and managing cities are required. Data produced by and about urban environments offer insight into what is happening in cities. Real-time data from sensors within the city record current transport and environmental conditions such as noise levels, water levels, journey times and public transport delays. Similarly administrative data such as demographics, employment statistics, property prices and crime rates all provide insight into how a city is evolving. Traditionally, these data were maintained separately and managed by individual city departments. Advances in technology and a move to open-government have placed many of these data in the public domain. Urban dashboards have emerged as a technique to visualise these data in an accessible way. This paper describes the implementation of one such dashboard, the Dublin Dashboard, an interactive website which collects, analyses and visualises data from a variety of sources about Dublin in Ireland through a series of interactive maps, graphs and applications. This paper describes the approach, the data and the technology used to develop the Dublin Dashboard and acts as a guideline for developing urban dashboards in other cities.
Bloomberg Businessweek reported late Tuesday that the Baltimore police have been subjecting that city to a vast and powerful aerial surveillance system since January, without telling, let alone asking, the public that they serve. This is a big deal.
This system, known as “wide-area surveillance” and run by an Ohio company called Persistent Surveillance Systems, involves the deployment of megapixel cameras on a Cessna aircraft, which circles over a city for up to 10 hours at a time, continuously photographing a 30-square-mile area and giving police the ability to retroactively track any vehicle or pedestrian within that area. It is the ultimate Big Brother “eye in the sky.” ...
Baidu, China’s internet search giant, has shown just what you can learn when you have access to enough location data. The firm’s Big Data Lab in Beijing has announced that it has used billions of location records from its 600 million users as a lens on the Chinese economy, tracking the flux of people around offices and shops as a proxy measurement for employment and consumption activity. The lab even used the data to predict Apple’s second quarter revenue in China.
The vision of the smart city, while alluring, is unlikely to serve the needs of the majority of urban dwellers. As India prepares for its urban awakening, it may be time for the government to stop dreaming
The FindFace mobile app, which makes it possible to find a random person's social-media page on Vkontakte after taking a photo of them in the street, has made news headlines for its use in experimental art projects and bullying women who appear in pornography. Meduza special correspondent Daniil Turovsky sat down with the authors of the “FaceN” technology that powers FindFace, and met with some of the technology's clients. It turns out that FindFace is just the beginning, and the underlying algorithm is based on a neural network that can actually help to identify any person in any photo or video, creating unlimited opportunities for an almost undetectable system of total surveillance. And Moscow's city officials, along with law-enforcement agencies throughout the country, are now expediting plans to put FaceN's technology to use.
Real-time data flows all around us. From ocean sensors to smartphones, the broad range of things that stream data to the Internet have one common characteristic—location. A geospatial platform brings data streams into a sophisticated mapping environment in which users perform powerful analysis and find new potential in practically every type of industry. Leading edge vendors provide big data technology that accesses and ingests high-velocity and high-volume real-time data for mapping and analysis. Companies that wait to step into the big data stream risk losing customers to those that have already adopted real-time data technologies. Bringing geospatial technology to the vast Internet of Everything (IoE) opens opportunities that are only visible within a geographic context....
The details of an ambitious plan from Google's sister company Sidewalk Labs to create entire "smart neighborhoods" just got a little clearer. According to Sidewalk Labs' pitch deck, which was obtained by Recode this week, the plan goes far beyond those free WiFi kiosks that are already on the streets of New York City. The kiosks will monitor everything from bike and pedestrian traffic to air quality and street noise. ....
Dashboards act as cognitive tools that improve a user’s ‘span of control’ over voluminous, varied and quickly transitioning data and enable a user to explore the characteristics and structure of datasets and interpret trends. The power and utility of city dashboards is their realist epistemology and instrumental rationality and their claims to show in detail and real-time the state of play of cities – to know the city as it actually is through objective, trustworthy, factual data; to translate the messiness and complexities of cities into rational, detailed, systematic, ordered forms of knowledge. In essence, dashboards enable a user to understand what is happening in a city system at any point in time and to act on that data – to steer the city through a set of visualisations and data levers in much the same way as a driver is presented with data via a dashboard and reacts accordingly. And if the data are made open then others can use the data to create business value and civic apps. While city dashboards seem to provide a powerful, new data-driven way to know and govern cities, they are not without critique....
Exclusive: Documents reveal Sidewalk Labs is offering cloud software Flow to Columbus, Ohio, to upgrade bus and parking services.
Sidewalk Labs, a secretive subsidiary of Alphabet, wants to radically overhaul public parking and transportation in American cities, emails and documents obtained by the Guardian reveal. Its high-tech services, which it calls “new superpowers to extend access and mobility”, could make it easier to drive and park in cities and create hybrid public/private transit options that rely heavily on ride-share services such as Uber. But they might also gut traditional bus services and require cities to invest heavily in Google’s own technologies, experts fear. ...
With the help of big data and analytics, urban planners can now use simulations to anticipate the impact of urban development programs. Using these tools, cities can become more sustainable and strategic, while the planning processes become ever more inclusive.
Our current smart-city techno fetish rides roughshod across the public realm. It encourages the belief that there’s always “an app for that” — that we can address deep-seated, structural urban problems through business-led technological innovation and somehow sidestep the messiness of inclusive politics.
To be truly smart, cities of the future should focus on developing democratic, participatory visions that harness smart technology to a shared agenda. Let’s create a genuinely shared urban commons and an inclusive public realm — not a place where quick adoption of smart technologies just reinforces the dominant-yet-dumb approaches of competition, enclosure, and division.
The quantitative data that’s available is far too limited, and likely to lead us to the wrong conclusions. When it comes to transportation planning, we have copious data about some things, and almost nothing about others. Plus, there’s an evident systematic bias in favor of current modes of urban transportation and travel patterns. The car-centric data we have about transportation fundamentally warps the field’s decision-making. Unless we’re careful, over-reliance on big data will only perpetuate that problem—if not make it worse.
Over the past decade the concept and development of smart cities has unfolded rapidly, with many city administrations implementing smart city initiatives and strategies and a diverse ecology of companies and researchers producing and deploying smart city technologies. In contrast to those that seek to realise the benefits of a smart city vision, a number of critics have highlighted a number of shortcomings, challenges and risks with such endeavours. This short paper outlines a third path, one that aims to realise the benefits of smart city initiatives while recasting the thinking and ethos underpinning them and addressing their deficiencies and limitations. It argues that smart city thinking and initiatives need to be reframed, reimagined and remade in six ways. Three of these concern normative and conceptual thinking with regards to goals, cities and epistemology, and three concern more practical and political thinking and praxes with regards to management/governance, ethics and security, and stakeholders and working relationships. The paper does not seek to be definitive or comprehensive, but rather to provide conceptual and practical suggestions and stimulate debate about how to productively recast smart urbanism and the creation of smart cities.
Data City | Data Nation will enable experts and developers in Singapore and London to come together to develop smart solutions to real-life challenges. The project will include the creation of a virtual data sandbox incorporating data from telcos, retailers, health providers, security firms and local government. The Data City | Data Nation initiative will build and provide managed access to billions of data points provided by the public and private sector and synchronised by time and location. Analysis of the data will deliver identification of trends and patterns providing insight into how government and business services are delivered in both London and Singapore. ...
When you think of Dublin, you probably think of friendly pubs and buskers entertaining pedestrians on cobblestone streets. But you should also imagine efficient, internet-controlled lighting in those pubs, and plan on enjoying those street musicians without having to navigate around littered sidewalks, or car-clogged streets. That's because Dublin is in the midst of a transformation into a smart city that leverages sensor networks through platforms focused on improving the city's infrastructure. ...
The Centre for Smart Infrastructure and Construction is building on advances in sensing technology to learn everything possible about a city's infrastructure – its tunnels, roads, bridges, sewers and power supplies
In this paper a framework is constructed to hypothesize if and how smart city technologies and urban big data produce privacy concerns among the people in these cities (as inhabitants, workers, visitors, and otherwise). The framework is built on the basis of two recurring dimensions in research about people's concerns about privacy: one dimensions represents that people perceive particular data as more personal and sensitive than others, the other dimension represents that people's privacy concerns differ according to the purpose for which data is collected, with the contrast between service and surveillance purposes most paramount. These two dimensions produce a 2 × 2 framework that hypothesizes which technologies and data-applications in smart cities are likely to raise people's privacy concerns, distinguishing between raising hardly any concern (impersonal data, service purpose), to raising controversy (personal data, surveillance purpose). Specific examples from the city of Rotterdam are used to further explore and illustrate the academic and practical usefulness of the framework. It is argued that the general hypothesis of the framework offers clear directions for further empirical research and theory building about privacy concerns in smart cities, and that it provides a sensitizing instrument for local governments to identify the absence, presence, or emergence of privacy concerns among their citizens.
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