We envision a future with information and data as the biggest driver of continuously increasing social and economic value. We seek a pivotal role in this change and believe in significant opportunities of the future data-driven world.
The City of Helsinki wants to improve its capability of obtaining a real-time view of traffic from multiple data sources. A real-time view of traffic is a graphic view of data related to traffic, lanes, the locations of means of transport, and conditions. It can provide a short-term forecast of traffic volumes, the smoothness of traffic, incidents, punctuality and prevailing conditions.
Tieto built the system required for the pilot project, supplied the equipment and developed a video analysis solution in collaboration with Tampere University of Technology.
Why is a real-time view of traffic needed?
Two main purposes were identified for traffic video analysis:
Analysis based on history data to support planning and decision making (data is collected in non-real-time over a longer period)
Analysis of real-time data to obtain an accurate view of incidents locally
Situation data based on a real-time view plays a central role in improving the smoothness and predictability of daily journeys and transportation as well as traffic safety. Data can be transmitted to end users, service providers and others who can benefit from it.
Traffic data collected over a longer period can be analysed so as to draw up forecasts of traffic flows and the effects of various incidents compared with the normal situation. Examples of incidents are traffic jams caused by major public events and accidents as well as poor weather conditions. Forecasts help in guiding traffic effectively immediately after an incident and preparing for the consequences.
Real-time analysis of traffic data also enables better services for city residents. Data on vacant parking spaces can be distributed to motorists involved in the system. Video material also reveals when it is time to clear snow from bicycle and pedestrian paths. The Finnish Transport Agency collects travel time data, requiring a lag of no more than one minute from the actual situation.
The goal: cost-effective data collection and analysis
Since a large number of mobile video recording units are needed to obtain a reliable and comprehensive real-time view, the system must be designed using as inexpensive equipment as possible.
That is why low-cost Android phones were selected as cameras that were attached to vehicle windscreens. Mobile phones are equipped with cameras of sufficiently high quality and built-in GPS tracking, making it easy to synchronize images with locations.
Phone sensors also provide data on acceleration, deceleration, vibration and other environmental factors that influence the usability of data. Off-the-shelf software is available and software customization is easy.
It is expected that the investment costs needed to improve the quality of the real-time view can be recovered through reduced costs of accidents, congestion and emissions, as well as through new business operations. The real-time view makes it possible to address incidents due to their rapid identification, positioning and forecasting.
Lessons learned form 60 000 observations
Some 60 000 observations were obtained for assessing the models. The system identified and classified the passenger cars seen in the videos with an accuracy of up to 95 percent. The identification percentages of other objects were lower.
To be useful in practice, the video analysis models need to be further developed. The analytics can be trained for desired purposes in order to increase the accuracy of results and expand the solution’s potential uses.
Today’s technology is not yet mature enough for real-time video analysis of big data. The main reasons for this are data transfer challenges (4G networks have insufficient capacity, so 5G networks are a must) and large data processing needs. If the real-time requirements are sacrificed, the solution is feasible as is.
Data transfer would not be a problem if analysis could be performed by the recording device. In that case, it would not be necessary to transfer all video material over the network for analysis; it would be enough to transfer metadata from local analysis, which requires much less capacity.
The future looks bright with data
The trial was unique in that data produced by mobile cameras has not been utilized very much to date. There were some flaws during the pilot phase – which was to be expected – but the results were interesting and quite encouraging, considering practical applications. The project provided valuable information on how methods of video image interpretation work and how suitable existing video recording systems are for producing traffic data.
From the perspective of further development, the availability, quality and analysis of data can be improved in several ways.
With sufficient incentives, it may be possible to crowdsource data collection – i.e. involve motorists in collecting data for analysis – by offering cameras with video analysis capabilities for private cars.
The number of static cameras at critical spots can be increased to help collect useful data.
Cameras can be installed on public transport to generate traffic data on the entire route network.
External data sources, such as accident data from emergency response centres, can be connected to the system to improve predictability and accuracy.
As the data-processing capacity of smartphones increases and the 5G data transfer system evolves, it will become possible to spread analytics over the entire ecosystem and, thereby, better meet the real-time requirements.
The City of Helsinki and Tieto will continue to look into new technologies and opportunities to leverage data, with the aim of providing better services for city residents.
All data processing includes extreme measures regarding information security, and personal data, such as names, identity numbers and addresses are concealed already during data collection. Encryption is used for all data transmission.
Public data has never previously been combined in the same way as in the experiment by Espoo and Tieto. The experiment is only possible thanks to the extremely precise public-sector information systems and high-quality data that exist in Finland.
Aiming to proactively identify people who need services
"The aim of the experiment is to combine information assets that had previously been separate in order to form customer and service pathways. We hope to find out whether artificial intelligence will enable us to identify residents who will need services at an earlier stage than we can now, while protecting the identities of individuals. In the future, it may be possible to allocate the city's resources more efficiently while improving the quality of life of individual residents, as they are offered preventive support," says Tomas Lehtinen, Project Manager, analyst at the Mayor's Office of the City of Espoo.
Espoo's data will be analysed and grouped by artificial intelligence for reasons of efficiency and information security. Artificial intelligence is able to process large amounts of data considerably more quickly than people. Artificial intelligence can be trained for this task in approximately one month, after which the computer can calculate results in a matter of hours or even minutes.
"We are trying to improve the understanding of people's service needs. This will help the city to provide more individualized services, thereby preventing problems such as social exclusion more cost-effectively. The artificial intelligence experiment, which will be carried out in the form of a one-off batch run, is one part in a series of experiments and development by Espoo, where we are providing tools for service development that covers the entire city and transcends departmental boundaries," says Päivi Sutinen, Services Development Director at the City of Espoo.
A world-class advancement in artificial intelligence utilization
"Espoo's experiment is a world-class advancement in the utilization of artificial intelligence and data. The data stored in Finland's various health care systems is unique. These extensive data resources should be exploited more extensively and used to provide higher-quality services for everyone in Finland," says Matti Ristimäki, Head of Health and Wellbeing area in Tieto’s Data-Driven Businesses unit.
The experiment will begin in the end of summer and it will be completed by the end of 2017. The experiment is one of Espoo's investments in the Six City project, under which Finland's six largest cities are jointly developing smarter, more open services based on the Six City Strategy. A further aim of the Six City Strategy is to create new expertise, businesses and jobs in Finland.
Tieto provides solutions to develop the Nordic societies with the most innovative technologies of today. Through Tieto’s artificial intelligence engine, it is possible to develop more personalized citizen services within social and healthcare area in Espoo. Tieto is developing artificial intelligent platform to provide exponential value for its customers in both public and private sectors.
Six City Strategy (https://6aika.fi/)
Matti Ristimäki's blog: Harnessing the new era of data in health for more human-centric wellbeing (https://enterprise.microsoft.com/en-us/articles/industries/health/harnes...)
For further information, please contact:
Päivi Sutinen, Services Development Director at the City of Espoo,
firstname.lastname@example.org, +358 46 877 2871
Tomas Lehtinen, Project Manager, Analyst at the City of Espoo
email@example.com, +358 43 826 9177
Päivi Huuhtanen, Head of External Affairs, Tieto
firstname.lastname@example.org, +358 40 753 7374
Tieto aims to capture the significant opportunities of the data-driven world and turn them into lifelong value for people, business and society. We aim to be our customers’ first choice for business renewal. In addition to our software and service expertise, we strongly utilize the opportunities presented by co-innovation and ecosystems.
Espoo, a network-like city with five urban centres, is a humane and responsible pioneer and a great place for anybody to live, learn, work and do business, and a place where every citizen can genuinely make a difference.
“The planetary-scale computer fed by a trillion sensors will drive a global industrial internet”, Larry Smarr, Professor, University of California, San Diego. This is both overwhelming and exiting at the same time.
I had the privilege to attend Realcomm IBCON 2017, Intelligent Building conference in San Diego California. I have to say that the ambience and mind set in a typically “old-fashioned” real estate industry is changing with big steps now. The excitement of the new era is hand felt. The real estate industry is being disrupted big time, and everyone who wants to survive has to get on-board.
If you want to keep your feet dry, connect everything with IoT
There are still many questions unanswered, and as many unasked but what seems to be clear is, if you want to keep your feet dry, connect everything with IoT and figure out a service model, this naturally goes for corporate working environments as well.
Matthew Toner, Managing Director, CBRE
What is the common factor being that we as humans are always searching for ways to make life a bit easier for us. Now with the possibilities provided to us with new tech such as AI, Robotics, Blockchain, the real estate industry as well is starting to figure out how to utilise these and make everything more effective. Connecting all dot´s and figuring out what possibilities we have with new tech is on all the player’s agenda. End game being in developing smart cities and what everybody seems to be doing is piloting the tech in smaller environments, take Qualcomm for example who has done major investments in their San Diego smart campus in order to understand the possibilities of IoT or rather IoE (Internet of Everything).
Utilising the data is what gives intelligence to the Intelligent Building
The market is looking for a solution that gives the brains to the building, this is achieved basically with sensors, but that is not enough. We need to understand what to do with the data as well.
For now, we have to make sense out of the data collected ourselves, in the coming years this will be automated and suggestions for actions will be given to us through AI. Again, the more we are able to connect, the more relevant information we get from the “hive” that is learning from each other, take Tesla for example where the “hive” is each and every car, the more cars on the road, the more intelligent the AI will get.
“Low hanging fruit is sensor data and machine learning. There is no excuse if you are not into that already”, Larry Smarr, Professor, University of California, San Diego.
We humans as are extremely good sensors for sensing the current environment, but we cannot be everywhere. To complete us and to be able to predict with deeper knowledge we have to connect with technology in a much faster pace and without boundaries.
Human centricity in all we do is not to be forgotten
New technologies provide extremely good tools to help us with our daily lives. Such as Tieto Intelligent Building solution, which is a great enabler in the Activity Based working environment, where you choose how and where to work based on your own activities. Human centricity in tech is having the right tools and sensors in place to make sense of the data and to help us in taking the correct actions. Connecting the data from the “building brain” is the key for making and intelligent building truly intelligent.
One big challenge is how to take different system siloes and piece it all together to make sense out of everything to make a holistic view of the environment. Qualcomm smart campus in San Diego has cracked this challenge, by connecting everything with IoT, even the outside solar panelled trashcans (which in the future smart cities will be wlan hotspots btw) has sensors to provide relevant information to the company picking up trash.
The water outlet for the fire department has a sensor to inform whether or not the system is functional, this saves up a lot of time for the county, as these maintenance checks have to be conducted systematically and all the time.
Healthy Buildings build on employee wellbeing
Finally, we are starting to hear even the real estate market talking about wellbeing and health, this drives the discussion towards human centricity where end users are the kings and queens.
The fact is that the essential bullshit detector of how a corporation values their employees is determined by their investment in space. This naturally put´s some pressure on the building owners & landlords, as corporations start to expect that the wellness factors are aligned with agreements. The space itself actually works as a recruitment tool for attracting and keeping talents.
Again, data and technology plays a big part in this as well, as we are able to validate the environments health through different methods, eg. biometrics through wearables. It delights me that Tieto Keilalahti Campus is a showcase in this matter as well, and we were actually mentioned in a topic discussion in San Diego by the panellist Ken Sinclair, who is a renowned author in the field of smart/intelligent buildings.
In a nutshell
Solutions need to:
saves time for employees
Amazing user experiences:
www.wrld3d.com - Dynamic 3D mapping platform for smart cities and buildings
www.sine.co - Intelligent Visitor and Contractor software
“You never change things by fighting the existing reality, to change something build a new model that makes the existing model obsolete” – Buckminster Fuller
Head of Concepts and Innovations - Facilities, Tieto