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Tiorc

TIORC is a partnership comprised of six Dutch organizations that specialize in energy efficiency within residential areas.
 
This plan focuses on tracking the energy consumption of any and all devices that utilize energy (electricity, heating, cooling, solar, gas, etc.), as well as studying how people interact with these energy sources. People are incentivized to save energy through gamification, while AI gathers data from their choices.
 
Even the most exemplary people can develop detrimental patterns of behavior over time, and this is where artificial intelligence comes in handy. AI is capable of completely automating and optimizing energy consumption while making sure that comfort levels are maintained.
 
Consortium invested in a test house and created a laboratory, where we have evaluated our solution in both simulated and authentic circumstances.
 
Together with Open University, we developed an AI model that seeks to understand and adapt to human behavior. Different people have distinct habits and energy needs in the home, so the AI must learn how to effectively imitate good behavior while avoiding bad behavior.
 
We added the German Company’s custom-made sensors to our product that allowed us to monitor and control each socket, light, or switch individually from a distance. AppsForce platform then handled all of the machine learning and remote management for every device in the home through its AI capabilities.
 
Using a mobile app and geo-fencing in conjunction with proximity sensors, we were able to identify user behavior. We wanted to take it a step further, so we linked our system to heating systems, hot water heaters, solar panels, batteries, and heat pumps.
 
For this venture, we have been awarded 3 European Union grants. If you are looking to make advancements in the energy sector, or need help with similar projects, please don’t hesitate to reach out to me.

TIORC’s ambition is to create zero energy consumption houses. TIORC is an EU-funded consortium project developed by AppsForce, OostNL, LIOF, Open University, IOX labs, Ubachs and EPM.

TIORC is an acronym for “Total Integral Optimal Renovation Concept”. TIORC will be using multiple products and sensors that are currently in development, interlinked with Artificial Intelligence. Through TIORC, we tackle wasted resources and reduce living costs for the owners, as energy consumption is brought to zero. Currently, TIORC is operational in one test-house, with more in development. As of now TIORC has received three EU grants for the development of each subsequent phase. AppsForce creates the AI as the centerpiece connecting and balancing all the products together.

The kind of energy and the way energy is used in a house differs widely among houses and inhabitants. Total energy use does not only depend on the energy-source (electricity or heating&cooling) but is also influenced by the behaviour of the inhabitants. There are many appliances available today that claim they make a house ‘smart’. A quick internet search shows companies like Sonoff (https://sonoff.itead.cc/en/) produce a range of smart sockets which can be used to monitor electricity consumption, have remote switching on, off, timers etc. Other companies provide measurement sensors like Ubibot (https://www.ubibot.io/) which can be used to measure everything from temperature to light.These devices are connected to cloud and can be connected to smart-home hubs such as Alexa, or even IFTTT.

The problem is that all these appliances gather information and do nothing ‘smart’ with it. There is no simple system that a user can install to control the devices and optimize energy use based on the data that was previously collected via the various appliances. They need to use mobile apps, or Alexa voice commands, to turn on or off devices, or create a timing schedule. This is possible if they spend extensive amount of time installing and configuring all devices. These systems then rely on the user to monitor and make decisions on energy use. Oftentimes users grow tired/bored of using such apps and they stop interacting with the system, ultimately making the system obsolete. Based on these observations, we developed research projects that will ultimately support the development of intelligent systems that really optimize the decision processes concerning energy use. These research projects focus not only on collecting relevant data concerning energy use in the house, but also analyzing the data and discovering patterns of energy use that take into account both energy source and inhabitant’s behavioral patterns in order to optimize energy use in truly smart houses.

Why is intelligence in renovation concepts important

The built environment, especially housing has a substantial contribution in the overall CO2-emission. This emission is being caused by the use of electricity, heating & cooling and hot tap water and of course the lifestyle of inhabitants. In a study conducted for the region Parkstad Limburg in 2015 was found that the built environment has a contribution of 66% of the joint CO2-emission in the region. From this 66% an amount of 37% is chargeable to personal households.

Reduction of CO2 in the built environment is necessary and possible when a good combination of physical measurements in the house itself is being realised on the one hand and on the other hand, the behaviour of the inhabitants is changed. With regard to this last point there has been research in which it is being established that behavioural change with regard to CO2-emission in the home-setting is a difficult challenge. The researchers found that inhabitants after 3 months, are not sensible anymore to change their lifestyle into a CO2-emission friendly way of living, to reduce their carbon footprint.

Now, the available systems on the market rely on users to constantly monitor data and make decisions on what to do concerning energy use. In other words, the systems collect data and feed it to the user for further processing and decision making. This is a novelty which wears off quickly and becomes an “information processing chore” for the users that ultimately will not optimize their true energy use. Basically, the existing systems relies on voice remote control, to optimize energy use, so you can say something like Alexa turn the lights off. These systems do not change how we behave, do not save energy, and do not use big data to analyse user behaviour and energy consumption.

Taking into account the intentions of the Dutch public & private partners that are united in ‘het Klimaatakkoord’, with regard to the built environment, then it seems that postponing of physical investments will be more and more difficult. But, integral with the physical investments, there should be a system that provides a full service to inhabitants, that supports them in living in a sustainable way, which is based on a self-learning algorithm. Such an integrated system, not only collects relevant data, but also uses artificial intelligence to process the collected data and identify patterns of energy use that take into account both the source of energy and its context as well as the inhabitants’ behavioral patterns. In this way energy use can be optimized in a truly “smart way”.

 

We built the electricity socket adopter, which is plugged in all sockets in the house. Electrical devices are connected to the adopters. The adopters are connected wirelessly to the central point and named – kitchen, fridge or bedroom tv. All sockets communicate wirelessly to the gateway, which is connected to the internet, allowing transfer of the data and receiving commands. Adopters measure voltage, amperage and wattage consumption and it is be sampled every 5 minutes (adjustable). The proximity sensors notify the gateway if they detect the movements, and gateway update every 5 minutes where the inhabitants are.

The cloud server with AppsForce platform communicates with TIORC mobile application. This application has APIs for gateway to connect to and transfer the data. The data is stored in the TIORC database for each house. The data is displayed on the dashboard with consumption data per every room and it can be drilled down to each socket. The dashboard has a historical data range selected by the user. The users are inhabitants but also TIORC companies which will analyze the consumption. AppsForce platform also uses push technology to issue shut down commands to socket adopters based on the instructions from AI.

AI is used to analyze stored data and detect two modes of electricity consumption – stand by and active. Lots of devices such as mobile phone charges, microwave owens, tvs etc consume energy even if they are off. AI will learn over the time the habits of inhabitants, detect if they are not in the room and if the device is on standby, and it will issue a command which will be transferred via AppsForce system to gateway and then to selected adopter to turn it off. This will save the energy. In case the inhabitant enters the room, the command will be issued to turn the device on.

In the average household there could be around up to 20 devices on standby causing average electricity cost between 5 and 25USD per device. However, if our system also switches of other devices such as table lamps or heaters for example, this saving can be even higher.

Mobile app for Android and iOS systems.

This app has standard user login and registration options, registration of the sensors, monitoring and reporting. The key aspect of the app is gaming. We setup the savings goals for the household. Basically, all inhabitants compete against each other and other households. We can have daily, weekly and monthly kings/queens of each room, household, neighborhood, city or country. Using the app is simple, user just needs to save energy – by switching off electrical appliances they don’t need. The saving is recorded and scored.