Self-sustenance and resilience is the need of the hour for our urban centres, we require the technology and intelligence to facilitate them. However, we are also required to contemplate on constructing cities with materials that can be used again. This blog by AICoreSpot delves into the notion of circularity with regards to our cities, how it manages its waste, and what implications that holds for our green earth.
United Nations estimates peg cities to consume 78% of the planet’s energy resources – additionally, our urban centres are responsible for 60% of greenhouse gas emissions. What’s shocking about these figures is that the fact that cities only account for a meagre 2% of our planet’s landmass. That’s miniscule. Estimates forecast that an additional 2.5 billion persons will dwell in our urban centres by the year 2050, a mere three decades from now. 90% of this population will be cities in Africa and Asia – the planet’s most populated continents. If we want to tackle climate change, we need to begin with our cities.
It is common knowledge that recycling is the procedure of gathering and processing waste materials – and then converting them into brand new products. The advantages are clear: minimize the quantity of waste, preserve our natural resources (which, surprise, are finite) and perhaps most importantly of all, conserve energy. Some less overt advantages can influence the bottom line of our enterprises. Recycling and reuse of materials within our cities can facilitate the manufacturing industry, while also improving economic security.
Let’s observe an instance, shall we? In the Houston area, located in the State of Texas, construction materials contribute to approximately 38% of the waste content. A majority of this could be converted and reused. The answer: circularity and reuse of materials when constructing our cities. By saving the resources till they can be leveraged by community groups, valuable materials can avoid the fate of landfills. This is where the Building Materials Reuse Warehouse steps in, a part of the City of Houston Solid Waste Management Dept. This not-for-profit entity takes in materials from citizens, supply companies and construction entities, and makes it readily available for reuse.
Initiatives such as these are amazing and a step in the right direction, but what if we could take this to the next level? What if we could actually leverage the material, return it, upcycle, and reuse it for the cause of new constructions? What if we could move tech development and resource innovation forward to develop a more circular, sustainable, smart city? Let’s delve deeper into what this might look like.
The Acceleration Consortium brings together the education industry, businesses, and the state to develop pre-competitive technologies for artificial intelligence-based laboratories for pre-competitive resources and molecular applications. The Consortium will tackle basic hurdles within deep learning algorithms and materials modelling, and practical matters of robotic control.
Consortium researches are also concentrating on materials and molecule discovery for a broad array of applications, from sustainable tech to drug discovery. Here are a few spheres they are concentrating on:
- Eco-friendly materials: Biodegradable recyclable polymers, plastics, and fabrics developed from the ground up for the cause of the circular economy.
- Transport and construction: Eco-friendly cement with a reduced carbon footprint, and lighter, more robust, corrosion-proof alloys and composites.
- Renewable, clean energy: Materials for energy production and organic flow batteries for large-scale energy storage.
This is just a sample of the work being carried out in materials science and engineering. We are witnessing the rise of criticality with regards to biodiversity, which accounts for the complicated and vital components of our earth. Some instances consist of species diversity, genetic diversity, ecosystem diversity, and functional diversity. When discussing this in the context of our cities, it is critical to identify restoring and improving biodiversity as being vital to enabling our cities to develop resilience in the wake the of the international climate crisis.
If we fail in this crucial mission, the consequences could be grave and drastic. We will witness ongoing infrastructure failures, power outages, food and resource scarcity, and other catastrophic disasters which are the inevitable outcome of climate change. This will influence exertion on the financial resources of our cities, and more importantly, lives will be lost. Hurricanes, forest fires, and other inclement events are only picking up pace, causing more casualties that ever before in human history. This is only the start – we are arguably, perhaps indisputably at a pivotal point in our history, one that could bring about a paradigm shift, or spell our eventual doom. If we don’t start making changes now, our cities will witness the consequences of this crisis. We need to make the shift towards circularity today, and if not, as soon as possible, and it begins with our urban centres.
Sustainability and circularity – the smart city of the future
Self-sustenance and resilience is the need of the hour for our urban centres, we require the technology and intelligence to facilitate them. However, we are also required to contemplate on constructing cities with materials that can be used again
5G myths and realities
In this blog post by AICoreSpot, we will discuss 5G and what avenues are present from facilitating ubiquitous connectivity. 5G can be revolutionary, catalysing self-driving vehicles and the Internet-of-things and making Edge Computing and AI (Artificial Intelligence) more widespread.
Quick RL via the composition of behaviours
Visualize that you had to go about learning how to chop, peel, and stir every time you desired to learn a new dish to cook. In several machine learning frameworks, agents typically have to learn completely from the ground up when encountered with new hurdles to surpass. It’s obvious, however, that individuals learn more effectively than this, they bring together capabilities learned prior
MuZero – Mastering chess, Go, shogi, and Atari with no rules
Half-a-decade ago, in 2016, we witnessed the introduction of AlphaGo, the first artificial intelligence (AI) program to best human beings at the ancient game of Go. A couple of years after that, its successor, AlphaZero, learned from the ground up in its efforts at mastering Go, Chess, and Shogi. Another advancement is in order. Enter MuZero, a considerable step forward in the cause of general-purpose algorithms.
Agent57 – beating the Atari benchmark
The Atari57 collection of games is a time-tested benchmark to evaluate agent performance throughout a broad array of activities. Agent57 is the first deep reinforcement learning agent to attain a score that beats the human benchmark across all 57 Atari 2600 games, the classic console of yesteryear.
Specification gaming – the other side of artificial intelligence ingenuity
Specification gaming is a trait that fulfils the literal specification of a goal without accomplishing the intended result. All of us have had brushes with specification gaming, even if not under this particular name.
Leveraging artificial intelligence to forecast retinal illness progression
Vision loss is a worrying healthcare concern for the elderly, approximately one in three individuals have some illness impacting their vision by age 65. Age-related macular degeneration (AMD) is the most widespread reason for blindness in developed nations. In Europe, nearly a quarter of individuals aged 60 and more are afflicted by AMD.
Traffic forecasting with sophisticated Graph Neural Networks
People are dependent on Google Maps for precise traffic forecasting and estimated times of arrival (ETAs). These are vital utilities that are particularly useful when you require to be routed to circumvent a traffic jam, if you are required to provide notifications to family and friends that you’re going to be a bit late, or if you require to start in time to reach a critical meeting.
Game theory as an engine for data analysis on larger scales
Sophisticated artificial intelligence frameworks tackle activities such as identifying objects in imagery and forecasting the 3D structure of proteins as a meticulous student would study for an examination. Through training on various instances of problems, they reduce their errors over the course of the time until they accomplish success.