#ASKotec; the 'Access to to Skills and Knowledge Open Tech Emergency Case' is a resource kit for community trainers, created for mobile field-use where there is neither easy power nor internet connectivity such as refugee camps, low-infrastructure regions or rural areas. Intended as ‘Open Tech for Good’, #ASKotec was created through a series of hub development workshops by a community of young innovators intent on bringing skills training and peacebuilding together in the effort to end the South Sudan conflict.
What has brought us together over the past year and a half is a wide-ranging and ever-increasing list of concerns about the project, not to mention growing frustration with a public engagement process that is unable to address these concerns effectively, given that it is led by and paid for by the company hoping to win “the big contract.”
Wish you had a better way to make sense of Twitter during disasters than this? Type in a keyword like #ChileEarthquake in Twitter's search box above and you'll see more tweets than you can possibly read in a day let alone keep up with for more than a few minutes. Wish there way were an easy, free and open…
In this audit, we obtained an understanding of the Commonwealth’s current IoT environment in terms of device use and planned use by surveying a sample of Commonwealth agencies (see Appendix) where we believed IoT devices were used for significant purposes.
In partnership with municipal crowdfunding platform Neighborly and the Berkeley Blockchain Lab, Berkeley City Council is planning on issuing municipal bonds on the blockchain.
Check out the world leading Air Pollution API. Educate and engage customers by enriching your products with Forecast, Pollen & Air Quality Data. View our Real-Time Air Quality Map and join the list of clients who trust us, including Dyson, Veolia and WeatherBug Learn more!
Villages in the Indonesian province of Aceh that have successfully reduced forest fires are to be rewarded through a clever new scheme that uses blockchain-based smart contracts. Here's how it...
The Centre for Collective Intelligence Design will explore how human and machine intelligence can be combined to make the most of our collective knowledge and develop innovative and effective solutions to social challenges.
We develop a computer vision method to measure changes in the physical appearances of neighborhoods from street-level imagery. We correlate the measured changes with neighborhood characteristics to determine which characteristics predict neighborhood improvement. We find that both education and population density predict improvements in neighborhood infrastructure, in support of theories of human capital agglomeration. Neighborhoods with better initial appearances experience more substantial upgrading, as predicted by the tipping theory of urban change. Finally, we observe more improvement in neighborhoods closer to both city centers and other physically attractive neighborhoods, in agreement with the invasion theory of urban sociology. Our results show how computer vision techniques, in combination with traditional methods, can be used to explore the dynamics of urban change.Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements—an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements—an observation that is consistent with “tipping” theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods—an observation that is consistent with the “invasion” theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities.
Building on our previous publication of similar high-resolution population maps for 22 countries, we're now releasing new maps of the majority of the African continent, and the project will eventually map nearly the whole world’s population. Using weakly- and semi-supervised learning.
FutureAir's first product, SAM™, is a Smart Air Manager that senses, manages and improves indoor air quality. SAM™ is designed by a world-renowned industrial designer, Ross Lovegrove. With proprietary sensing technology, SAM™ can identify the presence of toxins in the air, then initiate actions through an API with cloud computing; and, execute appropriate counter-measures to improve indoor air quality, comfort, and energy efficiency.
Holopolis MR imagines the uses case in the near future, when MR headsets are more popularized. It turns on the GPS with computer vision feature so that the users can bump into virtual public forums such as a forum setup next to the priority seats. Mature of mixed reality enables “engaging” civic engagement Despite the naming war of AR/VR/MR/XR, the substance of connecting information, overlaying visualization and designing interaction between real and virtual world brought us to a journey t...