Summer Night Smart City anyone? Ethics, Psychology and Artificial Intelligence in future city planning

ABBA’s famous song Summer Night City was released 40 years ago and was created as a tribute to happy and inspirational Stockholm. In 2017, the Stockholm City Council adopted a strategy City Vision 2040, developed together with its citizens, for making Stockholm the smartest city in the world. Would it turn Stockholm into a Summer Night Smart City?

Good songs and lively cities make us feel joyful, as they create a warm and safe space that encourage connection and collaboration. In music, one can experiment with sound arrangement by blending natural and artificial sounds using different instruments. In city planning, it is about “space arrangement” as one needs to anticipate the future uses of physical space, taking into account changing economic, environmental, demographic, cultural or transportation needs of citizens. The word citizen can even be fetched as the zen of cityness, or an urban feeling of connectedness.

Lately, the topic of Artificial Intelligence (AI) makes headlines everywhere. Despite the hype, the notion of AI triggers feelings of ambivalence since we are fascinated by the future benefits AI could bring for humans and society, yet uneasy about potential challenges related to their supposedly unprecedented capabilities. In the area of future city planning and urban development, we need to safeguard the quality of human lives, including human rights, citizens’ safety and security, city’s attractiveness, fairness and sustainability. To this end, we need to consider psychological, societal and ethical questions alongside the technical issues associated with AI’s rapid development and utilization. What if the technical development accelerates faster than the moral and psychological understanding related to AI applications? Moreover, people are not pixels: recent urban psychology research is concerned with cities being seen “mechanistically, as inanimate clumps of buildings and technology, which misses their essential human nature”.

Human experience and behavior are at all times contextual. The local rationality principle posits that we make decisions based on what makes sense to us provided the goals, local conditions and group norms, or the beliefs about proper way of acting in different situations. We are part of the context that affects how we act. How to ensure we, as humans, can deal with unintended consequences as long as AI collects and connects contextual clues, makes decisions and performs a range of activities? How about “sensemaking” for robots? Attachment theory refers to the dynamics of relationships and bonding: concepts such as ‘place identity’ and ‘place attachment’ suggest that the place we live has profound impact on our sense of self, belonging, purpose and meaning in life. Understanding how people interact with the environment and infrastructure in a city shapes a meaningful design and city planning. The future urban landscape needs to accommodate diverse and multicultural needs. Social identity theory indicates that ethnocentrism results when people categorize themselves into emotionally significant groups. In organization science, this can be related to the notion of faultlines, introduced a decade ago by Lau and Murnighan (1998) as hypothetical divisions based on different attributes, which can potentially trigger “us-versus-them” relationship dynamics. A typical big city abounds with multitude of differences of views, cultures or religions. How AI can be used to “melt” the faultlines, mitigate inequalities and build trust and sustainability? How to create cities with a healthy heartbeat, that we all love to live in?

“AI is just an extension of our existing culture”

One of the great promises of AI is to eliminate human weaknesses, such as cognitive biases in decision-making. The general assumption is that AI is logical and objectively rational. However, a new study that used a psychological tool such as Implicit Association Test shows that AI can be biased since it learns from humans: it acquires cultural biases embedded in the patterns of wording and effectively adopts cultural stereotypes. “AI is just an extension of our existing culture”, says Joanna Bryson, one of the authors in the study, a computer scientist at the University of Bath in the UK and Princeton University. A recent MIT study also found gender and skin-type bias in commercial AI systems. How a machine will decide what to do when facing ethical dilemmas? There is a need to encourage an active and genuine dialogue between technology experts and social scientists on how intelligent machines are impacting society. Now is the time to consider the “design, ethical, and policy challenges that AI technologies raise”, says Barbara Grosz, Professors at Harvard John A. Paulson School of Engineering and Applied Sciences. Prof. Grosz is chairing the AI100, the One Hundred Year Study on Artificial Intelligence, aiming at anticipating how the effects of AI will flow into every aspect of our lives.

ABBA was an awesome and adorable song-writing and singing “hit machine” with a lasting effect on generations. These days, ABBA is again under the spotlight in Finland for a good reason: the musical Mamma mia! will debut in Helsinki in May 2018 for the first time in Finnish language. Thrilling songs sound in thriving cities.


nad

Nadezhda Gotcheva
Senior Scientist
nadezhda.gotcheva(a)vtt.fi

Pysyykö tekoäly ihmisen hallinnassa?

Miten tekoälyn kanssa voi kommunikoida sujuvasti? Voiko tekoälyn kanssa tehdä yhteistyötä?

Nykyiset koneoppimiseen perustuvat tekoälysysteemit ovat usein itsenäisiä toimijoita, jotka tuovat johtopäätöksensä ihmisten tiedoksi mutta eivät muuten paljon ole vuorovaikutuksessa ihmisten kanssa.  Tekoälyä on tulossa yhä enemmän paitsi verkon kautta saataviin palveluihin myös liikkuviin koneisiin kuten autonomisiin autoihin ja robotteihin. On syytä miettiä, miten tekoäly varmasti pysyy ihmisen hallinnassa sekä miten ihminen voi ja miten pitää voida olla vuorovaikutuksessa tekoälyn kanssa.

Sanallinen ja sanaton viestintä

Teknologian trendianalyyseissa tekoälyn vuorovaikutusominaisuudet on tunnistettu seuraavaksi merkittäväksi kehitysaskeleeksi. Keskusteleva vuorovaikutus ei vaadi käyttäjää etsimään ja opettelemaan komentoja vaan oikea toiminto neuvotellaan vapaassa keskustelussa koneen kanssa. Vuorovaikutusta voi täydentää sanaton viestintä niin, että kone tunnistaa ja reagoi ihmisen tunnetilaan, kuten esimerkiksi siihen, että ihminen on ymmällään. Kone voi oppia tunnistamaan yksilöitä ja muokata toimintaansa sen mukaan, mitkä asiat ovat tälle henkilölle tuttuja, mitkä outoja, ja miten hän mieluiten toimii. Henkilökohtaiset virtuaaliapulaiset, kuten Applen Siri, pyrkivät luomaan suhteen omistajaansa ja oppimaan hänen mieltymyksensä niin, että pystyvät ajan myötä ennakoimaan ihmisen tarpeita ja tarjoamaan apua jo ennen kuin ihminen sitä ehtii itse pyytää.

Verkossa voi useinkin törmätä keskustelurobotteihin (chatbot). Ne ovat jo kohtuullisen taitavia ja niiden kanssa asioidessa ei edes heti huomaa, että vastassa ei olekaan oikea ihminen. Keskustelukyky perustuu siihen, että keskustelurobotti tuntee hyvin rajatun palvelualueen, jolla se toimii. Se on oppinut ennakoimaan, minkä tyyppisiä kysymyksiä ihmisillä on. Keskustelurobotti voi joskus tuntua vähän töykeältä, se johtunee siitä, että niitä ohjelmoivat ihmiset, joiden omat käytöstavat siirtynevät robotille.

Kiinnostus on kasvamassa sellaisiin tekoälyratkaisuihin, joissa ihmiset ja tekoäly toimivat yhteistyössä.  Ihmisten joukkovoimaa voidaan käyttää esimerkiksi tietojen keräämiseen tai kuvien tulkitsemiseen ratkaisuissa, joissa laaja joukko ihmisiä ja tekoäly muodostavat yhdessä toimivan kokonaisuuden. Globaalia älyä on käytetty esimerkiksi vanhojen tekstien digitoinnissa. Ihmissilmä on ylivertainen tunnistamaan sanoja oudoillakin kirjasimilla kirjoitettuna. Kun tekoäly tekee helpot tekstien tunnistamiset ja antaa ihmisten tehtäväksi epäselvät tapaukset, niin joukkovoimalla työ etenee vauhdikkaasti.

Sujuva vuorovaikutus vaatii  oppimista ja osallistumista

Ihmisen ja tekoälyn sujuvassa vuorovaikutuksessa riittää kehittämistä monella alueella. Tulevaisuudessa teollisuudessa nähdään yhä enemmän ihmisten ja robottien muodostamia tiimejä. Robotti voi toimia ihmisen apurina myös monenlaisissa huolto- ja palvelutehtävissä. Sujuva vuorovaikutus perustuu tekoälyyn, jonka avulla robotti tulkitsee ympäristöään ja ihmistä. Keskeistä on aikeiden tunnistaminen puolin ja toisin: ihmisen tulee pystyä ennakoimaan robotin toimia ja samoin robotin tulee ennakoida ihmisen toimia. Keskustelevia vuorovaikutusratkaisuja tarvitaan tälläkin alueella.

Autonomiset autot ja muut kulkuneuvot toimivat suurelta osin itsenäisesti, mutta kun eteen tulee pulmatilanne, tarvitaan helposti ihmistä apuun. Silloin on hyvä, jos ihminen on pidetty koko ajan tilanteen tasalla, jotta hän voi nopeasti selvittää, miten ongelmasta päästään yli. Aikeiden ilmaisu ja tunnistaminen on tärkeää myös sivullisten kannalta: kun jalankulkija kohtaa autonomisen auton, miten hän voi varmistua, että auto on havainnut hänet ja pysähtyy suojatien eteen antamaan tietä? Miten autonomiseen autoon saadaan katsekontakti?

Erilaiset älykkäät palvelut kodissa tai toimistossa pyrkivät täyttämään ihmisen toiveet ja ennakoimaan toiveita. Usein palvelut eivät näyttäydy ihmiselle, jolloin saattaa jäädä epäselväksi, miksi ilmastointi hurisee täysillä tai miksi lämpötila ei nouse. Tarvitaan sujuva vuorovaikutuskanava, jotta ihminen saa selville, miksi asiat menevät niin kuin menevät ja että asioihin voi vaikuttaa.

Tekoäly ei ole erehtymätön, se voi tehdä virheitä ja siihen voi tulla vikoja. Kun ihmiset oppivat ymmärtämään tekoälyn rajoitteet ja tekoälyn tavan päätellä ja toimia, niin vuorovaikutuskin helpottuu. Kun ihminen ymmärtää tekoälyn toiminnan perusteita, hän osaa asettua samalle tasolle sen kanssa, samaan tapaan kuin ihminen luontevasti virittäytyy ihmiskeskustelukumppaninsa tasolle.  Tekoälyratkaisuja on tärkeää kehittää niin että ihmiset, jotka tekoälyn kanssa tulevat toimimaan, otetaan mukaan ratkaisujen suunnitteluun.


Kaasinen Eija
Eija Kaasinen
Senior Scientist, VTT
@eijakaasinen 
eija.kaasinen(a)vtt.fi

Smart buildings as part of smart cities and societies

In order to reach clean and low-carbon future in cities, buildings need to become a proactive part of the urban environment. What this means is that they need to be highly efficient and allow for flexibility in their operations. All this requires new level of integration and smartness in the buildings themselves, and in their physical and digital connections with the rest of the urban environment.

Can I make my building smart with a mobile app?

Our smart phones already have all the necessary computing power needed to operate any smart home device. With them, it is possible to control, for example, lighting, heating and cooling, monitor your energy consumption, and detect leaks in water lines. All this can help you to manage and customize the conditions in your home and improve safety. However, a set of apps and gadgets do not equal to a smart building or ease of living. A smart building integrates all the building systems work seamlessly together in an optimal way and provides you your preferred living conditions without the need of apps. There are already examples of companies, who have entered the market by providing fully integrated service solutions. You can already buy desired indoor air conditions as a service, whilst enjoying cost and energy savings.

Will smart buildings result in smart cities?

Building-level integration and intelligence can enable significant building-level savings, while improving indoor conditions. However, the biggest benefits are found on the district or city-level, when two or more buildings are connected together with smart technologies. A simple example is connecting buildings with cooling needs, such as ice hockey rinks or server centers with buildings with heating needs, like swimming halls. These types of simple pairings have shown to bring energy savings of up to 40% with relatively simple technologies. On a district-scale, there are already projects in planning, where office and residential buildings are connected together through two-way district heating and cooling networks for even greater efficiencies.

What’s the demand-side management all about?

Buildings can store heating and cooling energy in their structures and systems, enabling them to operate without external supply of energy over short time periods without sacrificing their indoor conditions. When large enough heating or cooling masses are grouped and managed together, energy demand can be spread out more evenly, resulting in significantly lower peak demand. What this means for cities and energy companies is that once fully rolled out, demand side management can help to remove the need of some of the inefficient peak power plants. Ideally, this equals to lower emissions and lower cost throughout the value chain from the energy producer to the consumers.

Virtual power plants, today?

On electricity side there are already first commercial examples of large buildings operating in the electricity markets as virtual power plants. These types of examples are possible through a combination of integrated and automated building systems, combined with electricity storage and flexible loads inside the building. When such buildings are integrated to the grid, they can operate in the flexibility market. Likewise, aggregator business models, where geographically distributed smaller flexible loads combined together and connected to the flexibility market, are emerging.

What next?

Buildings can transform from consumers of resources, energy and services to active prosumers of all of these. This is where it all starts to make sense for the building owners, as there’s untapped revenue streams and savings that the new level of integration can bring. The examples are already many and the pace of change through roll-out of new business models is only accelerating.

If you want to read more about VTT’s vision regarding smart and sustainable cities, read our new white paper: Let’s turn your Smart City vision into reality.

Antti Ruuska VTT
Antti Ruuska
Business Development Manager, VTT
antti.ruuska(a)vtt.fi
Twitter: @antti_ruuska

 

Smart City development is inherently multi-technological and cross-disciplinary, and as an application-oriented research organisation VTT is an ideal partner. We work with the public sector and private companies as well as technology providers in research and innovation activities that expedites the development of smarter cities.  We can guide you from the early phases of vision-creation and concept development to practical implementations of smart outcomes.

How will we manage with artificial intelligence in the future?


What is machine learning? Why does artificial intelligence draw conclusions differently than humans do? How does artificial intelligence become superintelligence?

Early this year, I spent a night at a big hotel in Berlin. When I stepped into my room, it felt quite cool inside. There was a sticker by the door, telling that the hotel had introduced a ”Smart climate control” system and I could adjust the temperature to the desired level through my TV. I opened the TV and navigated to the climate control page through various turns. And there it was: the present temperature was 18 degrees and the target temperature set by the previous customer was 25. I set the target temperature to 22 degrees and went out to have dinner. When I returned to my room, the temperature had climbed to 19 degrees, probably due to my PC which I had left on in the room. It still felt quite cool, so I called the hotel reception for help. The help soon arrived. A janitor brought an old-style fan heater for my use. I could not keep the noisy fan on at night, so the temperature dropped back to around 18 degrees for the night. However, in the morning, I woke up well rested after a good night’s sleep. After all, you sleep better in a cool environment. This left me wondering that maybe the smart climate control was smart enough to understand better than I what was the ideal temperature for me. I would still have appreciated some kind of an explanation, because the “smart” system that does what it pleases without giving any say to a human left me feeling powerless. The hotel staff had also clearly resigned itself in front of the smart climate control and did not even try to fix the system in my room but resorted to using a good old fan heater. If the system really was smart, would it not also keep people up to date on the decisions it has made, telling what it is aiming at. If it does not function or cannot fulfil people’s wishes, would it not also give a reason for this?

From artificial intelligence to superintelligence

Artificial intelligence (AI) has been studied for decades, but now it is experiencing a strong renaissance. The earlier attempts to bring all expert knowledge on one subject into a single machine were defeated by their own impossibility. Today, the prevailing trend is the development of an AI based on machine learning, where the idea is that the machine learns little by little when being taught, but also on its own. Machine learning is well suited for the analysis of large masses of data and for supporting people in data-based decision-making. In medicine, for example, AI allows examination of different measurement data, and the machine can draw connections between data. Therefore, AI can be used for such a purpose as forecasting the development of a disease, when a patient’s data is compared to data on earlier patients. It is typical of machine learning that the result is not exact, but it is a probability-based forecast. That is why a machine cannot give similar detailed explanations for its conclusions as a human expert can.

A lot is expected of machine learning not only in medicine, but also in service business of companies, where AI can be used for analysing machine data collected from the field and forecasting, for example, occurrence of faults. In such applications, AI functions independently, analysing data and giving suggestions to people about the next necessary maintenance measures and even about their suitable timing, considering the financial factors.

In addition to these positive effects, futures researchers have also been painting some very gloomy scenarios about the “superintelligence” of the future that would be able to, for example, develop its own intelligence, draw its own conclusions and generate a will of its own, and could thus get out of the hands of both its designers and users.

What would be a potential path from the present machine learning-based AI systems to such superintelligence? AI is being introduced not only to services accessible via the internet, but also to mobile machines, such as autonomous cars and robots. Would this be the right time to consider making the future development paths such that the AI will remain under human control for sure?

A clever person solves the problems a wise person knows to avoid. This old wisdom should be applied to AI as well: if AI represents the cleverness and humans represent the wisdom, then humans must be secured a role in which they can prevent problems that AI might cause to itself or to humans. There must be an easy connection between AI and humans, and humans must have the final decision-making power. This prevents AI from getting out of human hands even as it learns new things.

In the next part of the blog series, I will focus more on the interaction between humans and AI.

Read more: VTT and Smart City

Kaasinen Eija
Eija Kaasinen
Senior Scientist, VTT
@eijakaasinen 
eija.kaasinen(a)vtt.fi

 

In the next part of the blog series, I will focus more on the interaction between humans and AI.

Proper design reduces the risk of damage to swimming pool buildings

Structural air leaks can increase the risk of moisture damage in indoor swimming pool buildings. The height of the pool area affects the moisture load in the upper structures. Temperature differences can cause indoor over-pressure, which increases the risk of moisture accumulation in air leaky structures. Design, implementation and the use of technical systems can have an impact on moisture loads and the risks they pose to buildings. Air tightness of structures and indoor air relative humidity levels are the key issues for moisture safety.

Temperature differences between inside and outside air tends to cause overpressure in the upper parts of swimming pool buildings which have a high inside open air space. This allows warm and humid indoor air to flow out via the air leakage routes along the ceiling and upper walls, causing moisture from the inside air to condense in structures.

The long-term build-up of moisture causes various problems in structures, such as the growth of mould or, at worst, structural weakening. Air leakages into structures tend to be at their greatest during winter, when the indoor air humidity level is greatest compared to outside, in turn creating the greatest risk of moisture accumulating.

uimahallit

Figure 1. The indoor air pressure conditions in swimming pools, caused by indoor air conditions and the height of the premises, pose challenges to the moisture performance of structures.

 

‘Rain’ from the roof into the interior may appear in swimming halls with poor airtightness of the structure. During cold periods, indoor moisture condenses and freezes in structures via air leakage routes and when the weather turns milder, the melted water runs into the inside air space via air leaks. In cases where the airtightness is this poor, there is an elevated risk of structural damage and it is very likely that impurities within the structures can enter the indoor air as the direction of the air leakage flows changes.

The pressure conditions in a high and heated space cannot be fully controlled by ventilation. Even if a typical level of under-pressure is maintained at floor level, long periods of overpressure can occur in the upper areas. For example, if the ventilation maintains a constant under-pressure of 10 Pa at floor level in a 9-metre high hall, overpressure will occur in the upper areas for almost half of the year (Figure 2).

Figure 2 The duration of the pressure difference between indoor and outdoor air in the upper parts of indoor swimming pools of different heights, when the indoor and outdoor air pressure is the same at floor level. Evaluation performed for a one year period in Helsinki climate conditions (nominal heating year).

 

The study conducted by VTT presents the principles of design, implementation and use of technical system, which can have an effect on the moisture loads of structures and the risks they pose. The key issue is to have sufficient airtightness of structures. In addition, the relative humidity indoors is set to the lower limits of the comfort zone during winter, around 40% RH.

Due to the high humidity of the indoor air, the risk of indoor air leakages through the structures is elevated in indoor swimming pools. A similar risk can be associated with other high hall structures, even if they typically have lower indoor air humidity than swimming pools.

The results presented are part of the ’Uimahallien yläpohjarakenteiden kosteustekniikka ja paloturvalliset PU-lämmöneristeiset hallirakenteet’ (Moisture Performance of the Roof Structures of Indoor Swimming Pools and Fire Safe Hall Structures with PU thermal insulation) project, which was conducted from 21 September 2015 to 31 December 2017. The study involved examining research data, guidelines and regulations related to the indoor air and structural moisture load of indoor swimming pools, and compiling expert views on the subject. In addition, the duration of pressure differences in high halls in the Finnish climate were analysed.

You can read the publicly available customer report here http://www.vtt.fi/inf/julkaisut/muut/2017/VTT-CR-06833-17.pdf

 

Tuomo Ojanen VTT

Tuomo Ojanen
Senior Scientist, VTT
tuomo.ojanen(a)vtt.fi

Energiaomavarainen kaupunki vaatii radikaaleja ratkaisuja

Tampereella tehdään jo tulevaisuuden kaupunkirakentamisen mallialuetta, vaikka uudisrakentaminen käynnistyy varsinaisesti vasta vuonna 2020. Kysymyksessä on 25 000 asukkaan Hiedanranta. Kaupunki on kutsunut Hiedanrantaan yrityksiä kokeilemaan ja kehittämään uutta liiketoimintaa, joille tunnusomaista ovat digitaalisuus, kestävyys, kiertotalous, energia tai ravinnontuotanto. Tavoitteena on saada alueelle 10 000 tulevaisuuden työpaikkaa. Energiaa alueen tulisi tuottaa yli oman tarpeen. Hiedanrannan kehitysohjelma on osa Smart Tampere -ohjelmaa.

Hiedanranta 4D Voimala -visiossa luovutaan kokonaan fossiilisista polttoaineista (Dekarbonisaatio) ja kiihdytetään energiatoimialan liiketoimintaympäristön uudistumista (Disruptio). Hajautetussa energiatuotannossa (Desentralisaatio) hyödynnetään aurinkoenergaa ja geotermistä energiaa sekä kierrätetään hukkalämpö ja biomateriaalit pienCHP-ratkaisuilla ja polttokennoilla. Kysyntäjousto ja erilaiset energiavarastot ovat tärkeä energiaälykästä rakentamista ja Hiedanrannan energiajärjestelmää. Siirtyminen keskitetyistä hajautettuihin ratkaisuihin vaatii reaaliaikaisuuteen perustuvia liiketoimintaprosesseja ja palveluja (Digitalisaatio).

Vainio_graafi

4D-VOIMALAN RADIKAALIT ELEMENTIT

  • Hiedanrannan Energiainnovaatiokeskus on keskeinen toimija 4D Voimalan ekosysteemien ja toimintamallien kehittämisessä.
  • Kilpailulle avoin infrastruktuuri mahdollistaa kaikkien energiavirtojen kaksisuuntaisuuden ja hajautetun ja holistisen energian tuotannon.
  • Ravintokierto osana energiajärjestelmää tuottaa kaupunkiympäristöön aivan uusia lähienergian-lähteitä, jotka integroidaan Hiedanrannan energiajärjestelmään.
  • Paikalliset sähköiset kauppapaikat ovat alusta kaupankäynnille paikallisten toimijoiden kesken. Kauppapaikat muodostavat valtakunnallisiin energiamarkkinoihin verrattavissa olevan ”mikroympäristön”. Energiayhteisö tai -osuuskunta on todennäköinen sidosryhmä tulevaisuuden energialiike-toiminnassa.
  • Ennustava reaaliaikainen energianhallinta kattaa kulutuksen ja tuotannon tarkan ennustamisen sekä koko energiainfrastuktuurin (tuotanto, jakelu, kuormat, kysyntäjousto, energian varastointi) ennustavan ohjauksen. Uusia teknologioita otetaan käyttöön tulevaisuuden liiketoimintaprosessien toteutuksessa – esim. lohkoketkut (Block Chains) ja tekoäly (AI).
  • Holistinen energiantuotanto hyödyntää kaikki paikalliset energialähteet huomioiden myös liitynnät ulkoisiin energiajärjestelmiin, energian talteenoton ja varastoinnin sekä kysyntäjouston (”virtuaali-voimalaitos”). Ennustava reaaliaikainen energiahallinta on tämän mahdollistaja.
  • Energiaälykäs rakennus on reaaliaikaisessa vuorovaikutuksessa sekä energiajärjestelmän että käyttäjien kanssa. Rakennus tai rakennusryhmät ovat siis kiinteä osa energiajärjestelmää – energian tuotantoa, jakelua, varastointia, ohjattavia kuormia ja energian kulutusta. Hiedanrannassa panostetaan alueellisiin ja rakennusryhmäkohtaisiin energiaratkaisuihin.

Hiedanranta 4D Voimala kuvaa tulevaisuuden toimintaympäristön, jossa kaikkien toimijoiden on oltava valmiita uudistamaan tuote- ja palveluportfolioita sekä liiketoimintamalleja. Energiatoimialan vireillä olevat EU direktiivit tulevat osaltaan edistämään 4D Voimalan toteutumista. Kaupungin organisaatioilta uudentyyppisen kaupungin rakentaminen vaatii tiivistä yhteistyötä energiainfrastruktuurin toteuttajien kanssa sekä tiedon ja osaamisen jakamista kotimaisten ja kansainvälisten kärkihankkeiden kanssa.

Hiedanranta 4D Voimalaa ovat olleet ideoimassa Tampereen kaupungin ja Tampereen Sähkölaitoksen kanssa VTT, Tampereen teknillinen yliopisto ja Tulevaisuuden tutkimuskeskus.

 

Markku Tuovinen
Markku Tuovinen
Senior Scientist, VTT
markku.tuovinen(a)vtt.fi
@TuovinenMarkku

 

 

Vainio
Terttu Vainio
Senior Scientist, VTT
terttu.vainio(a)vtt.fi