Thufir Hawat| Sustaining Our Planet for Future Generations
Sustaining Our Planet for Future Generations
Breaking Green
Summary
We build your city before it is actually built. We occupy it with citizens, but not real ones. We put it on a planet to measure its environmental impacts, but not our planet. How can that be done? Embrace ‘Breaking Green’, our solution to the above problems and more.
How We Addressed This Challenge
Controlling the impacts of environmental hazards and attaining an efficient use of creative tools to study their aspects is a must nowadays especially for cities: Cities being built and that will be built in the future should develop a clear green infrastructure before their real-life appliance. This ensures that those cities will have protective characteristics for their citizens, for the surroundings, and for the planet as a whole. Failing to do so would result in potentially catastrophic results that will harm people both short-term and long-term, hence our urgency to implement such a solution.
Our proposed solution takes a simplistic approach to the matter. You design your cities (put housing, flora, factories, governmental buildings, rivers, bridges, etc.), and by each addition, a set of scores alter, namely sustainability and greenness. Those scores change based on how each components trigger each other, taking in mind the environment in which the city will be built. Two simple instances of such alteration (and that actually do not depend on the environment) are: (1) you shouldn't put a factory near a river, and (2) for a given size of a city, a certain number of factories is too much. This all is calculated each time an edit is made to the city. But how can you edit?
We provide two options: Real-time AR collaborative editing and image recognition.
First, AR-Collaborative editing. This allows you to add components and edit them while standing above the city. We also allow that multiple people work on the same city simultaneously, for better inspection and more fun.
Second, image recognition. We provide a set of images that will be recognized by our app. The user can then use those images and edit them using any photo editing software such as photoshop, meshing the components as they like, and then scan the result using the app. The city will pop up in reality and the calculations will be made, giving the aforementioned scores.
With that, we hope to achieve a more predictable future for a city, giving you the assurance that this city will support you, your children, their grandchildren, on and on, for when the infrastructure is solid, the results, too, are solid.
How We Developed This Project
Science and Technology
The app uses the ARCore library provided by google to integrate 3D Models of the infrastructure of a city into the real world. AR was chosen due to its increased engagement-seeking from the user which adds the fun element to the experience by a casual user. However, even for professional use in planning, the AR element does not fail in representing the city being created, adjusting to real-world characteristics of the surrounding environment such as light intensity and coloring.
The 3D models are either created by us using Maya 3D or used from the public repository poly.google.com. Either way, they provide a clear representation of the underlying data making the user aware of not only the ongoing processes but also any looming danger on the city.
Using ARCore, Google's innovative answer to Apple's ARKit, the app was constrained from the start to be most functional and most entertaining. ARCore's APIs provided the app with the ability to track planes (where the city is placed), insert 3D models into the real world, calculate the required lighting and shadowing placed onto the objects, and collaborate with other app users to edit the same city in real time. Powering all of that was the language used, Kotlin, preferred for its simplicity, conciseness and interoperability with Java, the language of choice in the Android world. The only downside to using ARCore that one can think of is its exclusive availability on android. This will be addressed in future releases of the app that will use instead ARFoundation, Unity's encompassing API that abstracts away both ARCore and ARKit, allowing the use of the same code base to build to both platforms, Android and iOS.
The logic
Each object present in the city is given two numerical characteristics: a greenness value and a production value. The greenness value determines the environmental impact of the presence of that object in the city; it could be a positive value or a negative one. A negative value means that the object is harmful to the environment and vice versa. The production value determines the worth of that object in the city. This production value could represent energy production, food production, or both, etc. Again, it can be a negative number or a positive one: a negative value means that this object only uses resources and does not produce any, and vice versa. There can exist some patches that can affect those characteristics. For example, adding filters to a factory will increase its greenness but decrease its production, and so on.
Those values are not only dependent on the component itself, but also on the environment in which they are put. A frozen river doesn't have the same production value as a flowing one.
A group of arbitrary but related objects are called a unit. This unit acts on its own in terms of crises that can affect it. As such, a unit should contain a balanced amount of green and grey in order to decrease the risks of some environmental hazards such as floods and urban heat island effect and improve air quality. Such units that does not comply with those terms and does not have enough greenspace would have a warning that would require the user to take action.
Lessons
As has been stated in countless researches, predicting the consequences of simple infrastructural decisions on the environment can be hard, but not so much that we actually give up trying. Our simple take on making predictions is mostly intuitive, but also backed up by scientific evidence. One only needs to find the right source.
How We Used Space Agency Data in This Project
Nasa's data provide the ground work for the surrounding-aware city. Using geolocation, we gather from the data information that alters the production and greenness value of each components (not all components behave similarly in all locations). For example, if we learn that we are in a largely arid area with no rivers nearby, you wouldn't be able to put a river in your city. Moreover, if we learn that the soil is not suitable for crop growing, adding trees without adding first a nearby artificial water source wouldn't make much sense. This all is gathered from what we learn about the surrounding environment using Nasa Data.