With so many people working from home through lockdown, technology has become something of a go-to news story over the last few months. Covid-19 has already changed lives and accelerated the trend towards home working, and it just happens to coincide with the imminent arrival of superfast mobile broadband, in the shape of 5G.

One Scottish company, iOpt, already has a thriving business using existing LoRaWan networks to take the Internet-of-things (IoT) into homes. LoRaWan stands for Low Power, Wide Area (LPWA) networking protocol. It is designed to wirelessly connect battery operated ‘things’ to the internet in regional, national or global networks, and targets key Internet of Things (IoT) requirements.

Its importance for iOpt is that it enables the company to place humidity and CO2 sensors in homes and monitor the results centrally. This allows housing providers to monitor damp and household heating patterns as well as highlighting instances of fuel poverty (homes not properly heated).

According to the company’s CEO, Dane Ralston, existing networks are well suited to iOpt’s existing solutions. As and when 5G finally becomes commonplace across the UK, the new superfast wireless technology will simply provide additional scope for the company’s applications.

“There are two sides to the IoT wave,” Ralston explains.

“The first, which is already in daily use across the country, involves connecting ‘things’ in both homes and industry to supporting devices, typically apps on smart phones. The second, more futuristic wave, will need the massive additional addressing power of 5G to extend connectivity to a vaster array of things, from driverless vehicles to drones.

Today, iOpt is already making a name for itself providing ‘first wave’ connectivity.

“The bulk of our business is about providing information across housing association home portfolios and Local Authority housing stock,” he says.

Ralston says that this use of the IoT is “all about monitoring assets, making sure they are performing as they should and working optimally, helping to extend the usefulness and the life of assets”.One of the more obvious application areas involves expensive assets like aeroplanes, and high end cars, which is actually where iOpt initially focused its activities.

“This all started for me when I was doing audio systems for Aston Martin. We found we could use the car’s own network to see other data coming through the hi-fi, such as oil temperature, brakes and so on, and we could add a facility to send that information in real time to the garage, much as you see a Formula One car transmitting data to the team engineers as it goes around a racetrack,” Ralston remembers.

From there he went to work for Goodrich, in Prestwick, Ayrshire, doing much the same thing looking at data coming off aircraft engines. “You could see a whole bunch of key data, such as the number of landings and take-offs the aircraft had performed to date. Obviously, aircraft doing multiple daily flights between Scottish airports and London built up far more ‘cycles’ (take-offs and landings) than aircraft doing Transatlantic flights.

“That affects the health of the aircraft and determines maintenance intervals and the like. So on an expensive asset like an aircraft, that kind of connectivity between the aircraft and the operational centre is very important. But you can extend that to industrial applications and to portfolios of social housing, where you can create a lot of value for the organisation,” he says.

By installing sensors in housing association and local authority homes iOpt enables either the local authority or the housing association concerned, to see at a glance if there is an issue. “What we found when we started getting involved with social housing was that there is a real need to get an early warning if a house, for example, is not being heated properly so humidity and damp is building up in the property,” he explains.

Some tenants do not realise that high humidity and low temperatures can really degrade the fabric of a property over time. If this is allowed to build up the cost can run to thousands of pounds in repairs when the damage finally comes to the housing association’s attention. Using the IoT to monitor the property can therefore save the association significant sums.

“One of the really good things about this is that if it emerges that the cause of increasing damp and humidity in the property is that the tenant is experiencing fuel poverty, and can’t afford the heating bills, that is something the housing association or local authority can help with at an early stage,” he explains.
It is always going to be cheaper for a landlord to find ways of helping the tenant out of fuel poverty than to have to repair a property that is being damaged because it is not being properly heated through the winter. Early action will also have a very positive impact on the health of the tenant family, potentially saving the NHS considerable sums, and enhancing the well being of the occupants.

The IoT solutions provided by iOpt can also help with property management. If a property is supposed to be vacant and the heat sensors show that it is warmer than it should be, or if the housing association or local authority has had a motion sensor installed, that could trigger a notification for a site visit. Discovering that a vacant or abandoned property has been taken over by squatters is obviously going to be important to any housing association or local authority.

Ralston says that a number of iOpt’s contracts revolve around the client’s concerns about energy efficiency. “Organisations with social housing portfolios often need to get some proof that any energy efficiency measures that they have implemented are actually working properly,” he says.
For example, there has been a great deal of adverse comment in the press in recent years about some retrofit energy efficiency measures, such as loft insulation or cavity wall insulation.

“If insulation has been put into a home retrospectively, but it is not properly ventilated, then what tends to happen is that it simply traps more moisture in the property. Humidity sensors in the property will show this build up. When you see humidity levels climbing in a property, you know you are not winning!” he says.

“What we see sometimes is that the cause of rising humidity in a property is because a tumble dryer is being used constantly, but is not venting steam to the outside, but allowing it to escape inside the house, under the sink, for example.

“This can generate a tremendous amount of water vapour, leading to mold and damp.”

Sensors in homes and offices undoubtedly have an important role to play as the world of the Internet of Things becomes an accepted part of our lives. For example, sensor technology could play a key role for the NHS. “Our system could be used to get patients home safely and faster,” Ralston says.

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While many European states are currently setting up the 5th generation of mobile communication, scientists are already working on its optimization. Although 5G is far superior to its predecessors, even the latest mobile communication standard still has room for improvement: Especially in urban areas, where a direct line of sight between emitter and transceiver is difficult, the radio link does not yet function reliably. Within the recently launched EU project ARIADNE, eleven European partners are researching how an advanced system architecture “beyond 5G” can be developed by using high frequency bands and artificial intelligence.

A major advantage of 5G is its high frequencies and consequently its high transmission rate, which ensures an almost latency-free connection and fast data transfer. However, high frequencies require a directed system, which in most cases relies on a line of sight (LOS). This means that transmitter and receiver must be able to see each other. Unfortunately, the LOS principle can lead to connection problems, especially in urban and heavily developed areas.

One of the issues responsible for these connection problems in local 5G networks is the cancelling effect. This effect occurs when a signal is transmitted over a LOS connection and simultaneously copied via reflections. The copy overrides the signal from the LOS and cancels it. The result: the signal does not reach the receiver. This multipath propagation via non-line of sight (NLOS) remains a problem for 5G, as it did with its predecessor 4G. For this reason, one of the main aims of ARIADNE is the development of new concepts for better control of LOS and NLOS scenarios to massively improve the reliability of mobile communication links.

Higher efficiency and reliability of 5G

The EU Project, with the full title “Artificial Intelligence Aided D-band Network for 5G Long Term Evolution” brings together partners from research and industry from five countries. The aim is to develop energy-efficient and reliable mobile communication links based on frequencies in the D-band (130—174,8 GHz). With its aggregated bandwidth of more than 30 GHz, the D-band is perfectly suited for fast data transmission. However, this newly used band is divided into several sub-bands and requires an adaptation of the previously used system architecture and corresponding network control.

ARIADNE aims to create an intelligent communication system “beyond 5G” by combining an innovative high-frequency radio architecture and a new network processing concept based on artificial intelligence. By 2022, the project consortium plans to realize and demonstrate a radio link with extremely high data rates in the 100 Gbit/s range at almost zero latency. The European Union supports the project as part of the Horizon 2020 program. ARIADNE focuses on three major research areas: the development of hardware components, the research of metasurfaces and the adaptation of the network control based on artificial intelligence or machine learning.

Devices for a reliable D-band connection

Fraunhofer IAF contributes its expertise in the field of high-frequency electronics to the development of hardware components: together with partners, the Freiburg scientists are developing new radio technology for communication in the D-band (139—174,8 GHz). “Our focus lies on the development of new radio modules with highest spectral efficiency that capitalize on the frequency diversity and provide a control interface for optimization in the network. For this purpose, we will use our 20 nm InGaAs HEMT technology on silicon for the first time,” states Dr. Thomas Merkle, scientist and project manager on the part of Fraunhofer IAF.

Reflecting surfaces

In order to prevent network disturbances in NLOS connections, ARIADNE is researching metasurfaces and their potential for optimizing radio connections. Metasurfaces are adjustable reflectors for radio waves and are intended to counteract network-processing problems in urban areas. When there is no line of sight between base stations on rooftops and users in urban canyons, the metasurfaces will reflect the radio waves and thus ensure propagation outside the line of sight. A central network control will manage the metasurfaces.

“The concept of metasurfaces is already partially being used in 5G, but so far only for low frequencies. The higher the frequencies of the radio link, the finer the microstructures on the surface have to be. This makes the production of such structures very difficult for frequencies in the D-band,” explains Thomas Merkle. For this reason, the project team is researching the development of metasurfaces suitable for both high frequencies and industrial production. At Fraunhofer IAF, the scientists are working on so-called reflect arrays. These are small metasurfaces on antennas used for beam steering and focusing.

AI-based network control

In order to provide a constant and reliable radio link in all weather conditions, machine learning and artificial intelligence (AI) methods will be utilized for network management. Currently, classical mathematical methods are used for most mobile radio management. ARIADNE will employ AI-based algorithms for problem solutions in radio communication. While machine learning aims at a profound data analysis, AI will serve to develop a network control system that not only detects and reacts to problems, but can also predict and avoid them.

The ultimate goal of the project partners is to bring the individual project modules together in a test system and demonstrate its functionality. At the end of the project, they want to present two demonstrators as result of their research: The first demonstrator should achieve a reliable connection over 100 meters with a data rate of 100 Gbit/s in any weather condition. The second demonstrator is intended as a proof of concept under laboratory conditions, to show how a metasurface can improve the propagation condition of radio transmissions. This should prove the functionality of metasurfaces at high frequencies in the laboratory. At this point, the software development should demonstrate that the AI-based network control system can increase the reliability over the whole D-band network and guarantee the control of the metasurfaces.

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The recent issues of Australian and Amazon wildfires have raised a burning question – the technology that has been a major facilitator to human evolution and growth, could it not do anything to predict, manage or control such destruction? Its high time that technologies like AI, data science and 5G connectivity should take charge of climatic advancement as well.

The latest development in these technologies has shown some significant traits that can work for the betterment of the environment. Let’s see how they can serve nature and climate.

AI 

As noted by a report, the problem with climate change is that time is not on the side of humans — mankind has to find and implement some solutions relatively fast. That’s where AI could help. To date, there are two different approaches to AI: rules-based and learning-based. Both AI approaches have valid use cases when it comes to studying the environment and solving climate change. Rules-based AI is coded algorithms of if-then statements that are basically meant to solve simple problems. When it comes to the climate, a rules-based AI could be useful in helping scientists crunch numbers or compile data, saving humans a lot of time in manual labor. But a rules-based AI can only do so much. It has no memory capabilities — it’s focused on providing a solution to a problem that’s defined by a human. That’s why learning-based AI was created.

Moreover, learning-based AI is more advanced than rules-based AI because it diagnoses problems by interacting with the problem. Basically, learning-based AI has the capacity for memory, whereas rules-based AI does not.

When it comes to helping solve climate change, a learning-based AI could essentially do more than just crunch CO2 emission numbers. A learning-based AI could actually record those numbers, study causes, and solutions, and then recommend the best solution — in theory.

5G

According to Huawei, 5G networks can play an important role in mitigating climate change. At an event, Dr. Hui Cao, Head of Strategy and Policy, Huawei EU, underlined that “climate change is here, and we cannot afford to ignore it. Just like digital, green is a horizontal aspect of policy and business.”

Stressing that a facts-based approach would be key when measuring the impact of new technologies such as 5G, Dr. Cao pointed out that 5G consumed less energy than 4G. “5G power consumption per bit is a mere 10% of 4G. In other words, 90% of power is saved per bit,” he said.

The company in one of its 2018 reports stated four strategies for sustainability: digital inclusion; security and trustworthiness; environmental protection, and; a healthy, harmonious ecosystem. Over the past years, Huawei has been working to help achieve the UN’s Sustainable Development Goals (SDGs), build a sustainable and more inclusive ecosystem with its industry partners, and execute its own sustainability strategies.

Yingying Li, Head of Comms, Western Europe, Huawei, underlined that environmental protection was a key component in Huawei’s sustainable development initiatives: “Energy efficiency has become a major consideration for future communications networks. We have to use less energy to transmit more data while reducing the overall energy consumption of power systems. ICT technologies can help.”

Data Science

Furthermore, as noted by Towards Data Science, data science is going to play a big role in this huge battle. Finding new patterns in the data is a clear path to obtaining powerful solutions for this energy-hungry world.

Looking at data and finding patterns can dramatically help in finding often out-of-the-box solutions in every field, including Energy Efficiency.

Moreover, the cause of this huge energy usage is the need to keep the center at a certain temperature, avoiding overheating and breakdowns of the electronic components. As a consequence, if no clean energy is used to operate a data center, it can have a major effect on CO2 emissions. And let’s not forget about the cost of operating these places.

That’s why Deepmind (an artificial intelligence company acquired by Google) in 2016 succeeded in lowering energy consumption in a Google data center by 40%.

Also, several data-driven solutions are being tested to help lower greenhouse gas emissions and guide us to a completely renewable future. And many more are being studied right now.

Data Science has the ability to contribute to this battle and knowing how much it can do, it absolutely should.

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