In late-2015, the United Nations (UN) approved a 2030 Agenda for Sustainable Development, in which it includes 17 Sustainable Development Goals (SDGs). This approach focuses on “leaving no one behind”, emphasizing on a holistic approach to achieve a sustainable development for all, and the Internet of Things (IoT) can be a fundamental factor to reach these goals.
Within these 17 SDGs, sustainable cities and communities, affordable and clean energy, clean water and sanitation, responsible consumption and production, and good health and well-being are among them. In this sense, QNet with its IoT solutions can be a great asset to help us all achieve the UN sustainability goals.
Our solutions are founded within a decentralized model based on device clustering, where it is easy to add in new devices as nodes and makes it possible for any device to contribute computing resources over an intelligent mesh network so that computing can happen where it is needed and close to where it will be used.
By doing this we can assure a holistic, sustainable, and scalable approach towards smart cities and houses, energy efficiency, water and sanitation control, as well as, consumption and production, and a good level of health and well-being. A helpful solution that is possible because we acknowledge our solutions as a human first technological approach.
In this sense QNet performs within a decentralized blockchain that works through quantum safe tunnels using polymorphic encryption keys, and thus, has the ability for consensus to verify the data moved between the nodes over the tunnels, creating trusted data walled gardens. As such, it reduces the carbon footprint and provides solid security solutions.
To achieve these SDGs via IoT the QNet is constructed within an upper layer of the IoT, i.e. the Internet of Everything (IoE). This IoE works through a well-designed Edge platform that drives distributed computing, and as a natural consequence strives away from the monolithic or centralized infrastructure currently used.
This means that the Cloud (Server Farm) becomes unessential and, thus, liberating the system from the massive energy costs that centralized servers currently input into Planet Earth. Attaining such a level of the Internet of Everything actuating as the director of the Internet of Things inside an Edge Computing platform decreases exponentially the tech environmental footprint.
Internet of Everything Corp’s Eden System is sustainable through its aforementioned decentralized nature, which allows for functionality onsite. Resulting in various benefits that are crucial to achieve the UN’s SDGs:
· Decrease in bandwidth.
· Sustainable AI computing.
· Data to information refinement.
· Real-time information.
Deploying a decentralized digital infrastructure, as IoE Corp Eden, means that the data generated by IoT devices doesn’t have to be moved in its totality to server centers. This reduces the data traffic substantially, which in turn mitigates the bandwidth issue, therefore Eden reduces network traffic and data center usage.
With Eden, the amount of data traversing the network can be reduced greatly, freeing up bandwidth.
· Bandwidth — Is a measure of the quantity/size of data a network can transfer in a given time frame.
Bandwidth is shared among users and, as such, the more data sent via the network at a given moment, the slower the network speed. A situation that, within IoT devices for smart cities, is not acceptable because smart cities generate critical data that needs to be accessible in real-time.
To solve this problem, data on the edge is much more likely to be useful and, in addition, used on the edge, in the context of its environment. Instead of constantly sending data streams to the cloud, which on many occasions is not necessary, it, therefore, makes sense to work with the data on the edge and make information available to services that can request it as needed.
A clear example of this, is a smart city's traffic intersection that is constantly being monitored by thousands of cameras. And during the 24-hours of the day, the flow of traffic has no major incidents, therefore, moving all this data to a server center is not sustainably-efficient. Because, there are many hours of the day when the intersection has no traffic at all, making the data traversing senseless.
Why? Well, first it will retain bandwidth, which can result in latency, and it also competes with other traffic intersections that might have critical information at a given time, e.g., an accident. Having this risk potential makes the processing of data through server centers an inviable solution for IoT deployments in smart cities.
In relation to the bandwidth issue, sustainable AI is also a problem when thinking about reaching the UN’s SDGs. AI and Computing are, currently, huge consumers of energy, to the present extent that it has increased 300,000-fold from 2012 to 2018. A fact, exemplified, when training an AI language-processing system that consumes as much energy as a return flight for one person between New York and San Francisco.
To be able to decrease this type of energy consumption, and subsequently reduce the carbon footprint AI computing is generating, there are certain procedures that need to be taken into account. One of the basic thoughts that need to change is the concept of an AI system built only for performance goals, sustainability has to be embedded into the functional and business requirements of AI projects. To be able to act upon these present problems within AI, sustainable AI indicates that, to make the systems carbon-aware and carbon-efficient, we have to:
· Elevate smaller models
· Alternate deployment strategies
· Indicate optimal running time
· Work within certain locations
· Election of hardware
Another vital factor that affects the sustainability of AI computing for IoT devices deployment is the selection of programming languages. Basically, there are two options for the translation of programming languages to machine language, which is binary (1s and 0s), and these are compiled and interpreted. Research has shown that compiling language is more energy-efficient in comparison to interpreting language, therefore, the use of compiling within IoT devices deployment is a better solution to optimize sustainable computing.
As we explained, AI processing can be very wasteful and leave a huge carbon footprint, but at the same time, we have to acknowledge that AI is a driving force within IoT. Given this reality, there has to be a balance, and this balance comes through the implementation of data to information (D2I) refinement. Going back to the example of traffic intersections in smart cities, and the need to move all the data to server centers to be analyzed, processed, stored, and then delivered back to the source, creating bandwidth capacity issues.
Let’s look at it from the AI processing point of view, having data centers’ AI process huge amounts of data from an intersection, with no critical data, results in a huge economic and sustainable cost. But, having on a local level an AI capable of D2I refinement, eliminates the costly burden of cloud processing. Also, as it is a well-designed edge computing platform it is able to function without an internet connection, enabling real-time response rates.
Another example of D2I refinement is seen within smart home IoT devices, like a thermostat, which produces 1000s of data points every minute. Taking into account that this data offers minimal changes, it isn’t necessarily critical and doesn’t need to be in the cloud and accessible from anywhere. With D2I refinement working on clustered edge computing, this type of information can perform fast, efficiently, and autonomously from an internet connection.
Having all the above, working at a sustainable level and locally, offers the benefit of accessing real-time information when needed. A fundamental aspect when it comes to achieving the UN’s sustainability goals because it makes the digitalization of IoT infrastructure more efficient. As is the already mentioned traffic intersection example. Being able to keep data and process it at a local level, results in real-time data to information.
This means that first responders to traffic incidents can actuate on a real-time basis, reducing the time to reach the traffic incident, e.g., an accident or traffic congestion. These are critical situations that need first responders to arrive as quickly as possible, and cloud providers cannot assure real-time D2I on a 24/7 365 day basis. The reasons for the incapacity of cloud providers to assure real-time information comes down to the mentioned bandwidth problem, but also to server malfunction or internet connection outage.
In contrast, clustered edge computing with knowledge of AI-driven D2I at local levels and within a decentralized network, does assure IoT devices can perform on a real-time basis. This is possible because being decentralized all the devices and nodes are capable of performing independently, therefore if one device or node is malfunctioning, another can produce the required D2I.
In conclusion, implementing IoE Eden System as the orchestrator of IoT deployment for smart solutions, such as a smart city, helps to achieve the United Nations SDGs. With this decentralized clustered edge computing, AI-driven, data to information refinement, set in place, the ITC carbon footprint can be reduced. It also acts on the great benefits that IoT devices deployments can offer to all industry verticals, governments, cities, and individuals.
Helping to create through digitalization a world that is more aware of energy usage, better equipped to act on energy-inefficiency, and social inequalities, both basic requirements within the UN’s SDGs. It is of vital importance to take into account this innovative approach if we want digitalization to be a real game-changer when it comes to a future world where sustainability isn’t an issue but part of our everyday life.
The potential of IoT, to help us all achieve the UN sustainability goals, has already been exposed, the next step requires a transformation of the digital infrastructure. Implementing our Eden System helps accelerate the IoT deployment on a global scale, eliminating the huge obstacles, server centers are currently confronting. Issues that have to do with the increase of the carbon footprint:
· Information and Communications Technology could create up to 3.5% of global emissions by 2025 — surpassing both aviation and shipping.
As stated earlier, IoT can solve problems for mankind with smart solutions, but those solutions need to be sustainable, and currently, they are not. There is no point in solving a City’s traffic problems and reducing pollution if the solution is not sustainable. At present, it means that if the solution relies on third-party systems, or utilizes computing that has unfixed pricing, smart solutions are destined to become burdens for cities and other installations.
IoE Corp Eden is ready to begin the transformation, giving IoT devices software to thrive, and produce great benefits for humankind. Our decentralized, autonomous, portable, secure, virtual infrastructure for managing clustered workloads over depos (decentralized pods) and services that facilitate both declarative configuration and automation. It is the digital evolution that needs to be understood and implemented throughout IoT devices, in this way UN’s SDGs are reachable.