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IoT Search Engine Concept Pitches
Work created with Scenes™ by SAP AppHaus
(https://experience.sap.com/designservices/scenes)
Room Booking
Currently, booking systems don’t register if a user shows up at their
reservation, thus creating the illusion to other users, that the rooms are
booked.This creates frustration and distrust towards the system.To
compensate the distrust, students manually check every room.
The students/employees etc. needs a solution that provides an overview,
and instant live updates on rooms availability to gain the trust for the room
booking system.
Scene 1: Campus rooms seem to be unavailable
Room Booking
This room is booked
Ahh! This
University
seriously need
more rooms!
This room is
booked
But
Not used!
Scene 2: IoTCrawler can find available rooms
Hey students! Check your phone! I can tell you where all the
available rooms are, even the nearest ones to minimize downtime!
Room Booking
This room
is booked
But
Not used!
This room
is booked
But
Not used!
This
room is
booked
But
Not
used!
This room
is booked
But
Not used!
Thankfully the IoTCrawler can see if rooms are being used even though they are booked!
Scene 3: How does it do it?
Room Booking
The IoTCrawler crawls the IoT network at the campus and the then calculates
the situation. It can tell if the rooms actually are used despite being booked &
also scan unbooked rooms to see if they are actually being used.
This room
is booked
But
Not used!
This room
is booked
But
Not used!
Hey students! This is your options today:
• Room 265 is available in 30min.
• Room 306 is not being used right now.
• Room 102 with the projector is available from
13.00-14.00
• The travel time from “home” is approx. 25 min.
I think we need
a projector
today…
Scene 4: A solution is provided to the students
Room Booking
The IoTCrawler detects a booked room for the entire day, but since no
one showed up and claimed it (In compliance with the rules) The
students can take over the room and book it for the remaining day…
*BiB BuuP*
Go to room 265, its
available all day!
Hey guys check it out!
Apparently, there is a lot of
rooms! The IoT Crawler
knows the way!
This room is
Re-booked
And now
soon in use!
Together with sensors, the IoTCrawler collects information and translate
them into readable content.
The sensors sends information about movement in rooms, allowing the
Crawler to estimate whether people are present or not.
Furthermore, the Crawler checks the booking system and compile the data.
This allows users to gain insight on what time of the day, that they will be
most successful with obtaining rooms.
IoTCrawler
SmartConnect
Smart Home environments are extremely heterogeneous, each
vendor uses its own technology and data representations.
Smart Home application developers are spending considerable
amount of time with the integration of vendors specific APIs. This
restricts the scalability with respect to supported devices and smart
home systems. Ultimately Smart Home users suffer from limited
number of Smart Home solutions.
On a technical level it is important to address the challenge of
semantic interoperability and accelerating the integration of Smart
Home devices. IoTCrawler provides a promising framework for solving
this challenge in the Smart Home domain.
Tom, Tech-Savvy Smart Home User, has found the GrowSmarter Energy Awareness application,
however he cannot use it. The application doesn’t support the type of sensors that he has.
Scene 1: Tom often experiences problems when he is trying to connect the
different sensors in his Smart Home to a new application
SmartConnect
Supported sensors
How can I
connect my
sensors to GS
Dashboard?
Unsupported
Scene 2: The IoTCrawler enabled functionality “SmartConnect” automatically recognizes new
sensors
SmartConnect
IoTCrawler checks with Tom whether the devices have been correctly recognized and integrates
it so that they can be accessed by application like the GS Energy Dashboard
Tom, I recognized that you
have three smart plugs that can
measure energy consumption.
Is that correct ?
Yes. Exactly!
Scene 3: Now Tom can get insights about his energy consumption …
SmartConnect
Cool! Now I can use
GS Dashboard with
my sensors to learn
about my energy
consumption
With the help of IoTCrawler and SmartConnect, Tom use GS Energy Awareness Dashboard
with his Smart Home System.
Scene 4: …David who developed the GS Energy Awareness Application
also benefits from IoTCrawler’s integration functionality.
SmartConnect
Wow! With IoTCrawler I
can reach many more
users with the same
effort
With the help of IoTCrawler and SmartConnect, David’s application can be used by many
more users with the same effort.
Without IoTCrawler
With IoTCrawler and SmartConnect
SmartConnect relies heavily on IoTCrawlers Smart Home
Crawler capability. It crawls Smart Home networks, interacts
with home owners, data integrators, or uses crowd sourcing
for fast integration of discovered IoT devices into
IoTCrawler‘s semantic Metadata Repository (MDR) based on
which indices and rankings are created.
Applications can thus focus on the data rather than devices
and have the potential to provide interoperability with a
larger amount of smart home devices.
IoTCrawler
Elderly Care
Activity patterns and changes to the daily living routines can indicate
changes in health and well being.
Monitoring physiological and environmental data from home and
analyzing trends can lead to create personalized care and intervention
plans.
The work requires IoT and sensory data collection, time series data
analysis, machine learning and effective ways of communicating
actionable information with people, their relatives, care and clinical staff.
The challenge for users is compliance, acceptance and complexity of
interacting with the technology.
Anna, an elderly dementia patient, goes out and she forgets her
keys. Carla, Anna’s daughter, is worried about where her mother is.
Scene 1: Dementia patient going out
Where am I??
Where are my
keys?
Elderly Care
IoTCrawler crawls information from sensors in Anna’s house to
detect any changes and collects the data.
Scene 2: Crawling sensors in the home
Elderly Care
11 a.m.
Room 1
No one is there
11 a.m.
Room 2
No one is there
10 a.m.
Kitchen
Making coffee
Crawling
Room 1
Room 2
Kitchen
Scene 3: Checking dementia patient status
Elderly Care
With IoTCrawler I can realize
when my mother went out
and if it’s late I can call for
help. I can also see when the
sensors in her home needs
maintenance
Elderly Care – UI example
IoTCrawler provides methods for extracting patterns and trends from
continuous data:
machine learning models to interpret the patterns and create algorithms to
detect complex conditions:
Personalised and privacy´aware search and discovery methods for highly
sensitive data:
IoTCrawler
Smart Parking
Finding a free parking spot can be frustrating,
time consuming and generates pollution. At the
same time it feeds-back by worsening traffic
congestion.
The challenge is to help users find a free parking
spot that fits their duration, distance and budget
constraints.
Scene 1: Current situation in Murcia
SMART PARKING
Julia lives in Corvera, a 30 minute drive to Murcia, where she
works. If Julia leaves later than 7:30 there are often no free
parking spots in her destination area.
No free parking
spots!
I’ll never make it!
Scene 2: IoTCrawler-based Smart parking service
SMART PARKING
Julia has heard of this new app… it uses… Crawling
Regulated Parking Zone info
Crawling RPZ info:
Expender1: Busy
Expender2: Free
Expender3: Free
Scene 3: Crawling
SMART PARKING
The service uses the functionality of the IoTCrawler by
crawling Regulated Parking Zone information (RPZ).
10:00 a.m.
Sector 2
#60% Free
(likelihood)
10:00 a.m.
Sector 1
#90% Free
(likelihood)
10:00 a.m.
Sector 3
#10% Free
(likelihood)
Crawling
Sector1
Sector2
Sector3
Scene 4: Julia has a great morning commute.
SMART PARKING
With the IoT Crawler compliant app Julia’s
commute will be much less stressful. The
application will also readjust if traffic jams happen.
There's a lot of
traffic. But, I’ll
make it in time.
IoTCrawler gathers information on the different
parking alternatives, indexing and ranking them
according to parameters relevant to the user.
When queried, it returns updated and precise
information, allowing us to offer flexible and agile
suggestions to the user.
IoTCrawler
Pop-up Experimentation Space
The concepts are based on insights from the collaboration phase.
We focused on Aarhus’ Smart City lab – our outdoor testing area
for smart city solutions.
In a workshop with a neighboring high-school we found out that
dream of a greener Aarhus City Lab and that it might be used for
sustainability experiments. Their ideas for monitoring and
plants in this public space, could also be used to support biology
innovation class.
Through interviews and workshop with IoT startups and Smart City
stakeholders, we found out that there is a need for
and a better overview of the options.
We build on the potential we see in easy access to flexible areas for
and testing IoT experiments – for formal, informal and
– by using IoTCrawler functionalities.
Concept 3: Pop-up
Experiment space
Subject:
Sustainable
innovation &
IoT solutions
The innovation teacher Patrick from the local high school has planned to
work with IoT over the course of 8 lessons with the students. He wants
the lessons to be connected to real-life needs and environments.
Tomorrows
lesson starts
at 9:00 at
City Lab
Don’t be late!
Scene 1: The high-school has a need for an outdoor area for
an experiment with IoT
Pop-up Experimentation Space®
Concept 3: Pop-up
Experiment space
The next day and the week after
the students work on their IoT
solutions and they setup
experiments in the Pop-up
experiment space.
Scene 2: They use the service “Pop-up experiment space” to
find an experiment space nearby.
Pop-up Experimentation Space®
Concept 3: Pop-up
Experiment space
The sensors are placed and activated.
The monitoring system is setup online.
Scene 3: The students carry out their experiments.
Pop-up Experimentation Space®
The sensor data is released for others
to see and the municipality use it to
know when to water else-where in
Aarhus.
The IoTCrawler makes it possible for
the municipality and citizens to track
and use external data sources.
Scene 4: The data from the IoT sensors are easily available on
the Pop-up experiment space platform.
Pop-up Experimentation Space®
Pop-up
Experimentation Space®
SubscribeJoin
The IoT Garden
Join Katedral School and
others exploring
sustainable IoT solutions…
[Read more]
Create a new Experiment Space
Manage an existing Experiment Space
Search Experiment Spaces
E.g. ”IoT Garden”
Subscribe
Join
The IoT Garden
Join Katedral School and others in exploring how IoT Solutions
can support sustainability in the cities. Join this space if you want
to add your own sensors or IoT solutions – follow the rules and
guidelines for experimenting in this space. You can also subscribe
to the data feed from this experiment space.
Experiment Dashboard
Experiment Updates
Suggested: Surrounding Data
Testing Smart Bench Garden sensors Smart Compost Bin
Experiment Space Rules
• All ideas need to be approved by the City of Aarhus since this is a
public space. After joining you can apply with a solution.
• All solutions should be mobile or easy to remove.
• The solutions may not interfere with the everyday use of the area.
Create a new Experiment Space
Manage an existing Experiment Space
Search Experiment Spaces
E.g. ”IoT Garden”
Last Crawled: 2 hours ago by IoTCrawler
Soil-moisture Sensor Quality Metrics
Latest Value and Time Stamp
Traffic Noise Quality Metrics
Latest Value and Time Stamp
Pop-up
Experimentation Space®
IoTCrawler crawls the geofenced area that defines the experimentation
space and automatically integrates all IoT sensors and devices from users
who have been allowed to be part of this particular experimentation
space.
A user can subscribe to the data generated in the experimentation space,
which IoTCrawler delivers and monitor its quality.
IoTCrawler
CompariSense
In the early stages of an IoT startup’s product development there
is a need to find out if the product generates valid data by
comparing it to other data sources.
E.g. for parking sensors, startups could use webcams as to way
to identify if a car is parked.
or if you are measuring air quality there might be
existing/competing products in a city that could be used to
benchmark your product.
The concept “CompariSense” give IoT startups and their
customers an easier way to test and benchmark IoT products.
Scene 1: Vicki runs an IoT start-up and has created a new
IoT product that measures UV levels.
CompariSense®
Vicki needs to verify that the data her products generate is valid. Normally she would compare the data from her
IoT device with data from other sensors she has made or a reference data set that a customer asks her to use.
Scene 2: This time Vicki uses a service called CompariSense
to validate her data.
CompariSense®
She searches for UV sensors on the CompariSense platform and a list of available UV sensors shows up.
She saves them to her profile on CompariSense and starts monitoring them along with her own data to
validate her product.
These UV sensors are
just what I need in
order to test my
product.
CompariSense®
CompariSense®
UV
Scene 3: Vicki monitors the data and sees an anomality
CompariSense®
Vicki can see that her own data spikes on certain times of the day compared to the other sources,
so she explores the problem and identifies a solution.
Hmm…. My
measurements seem
to be a bit off
compared to the
other data sources.
Selected Public
Data Source
(Virtual sensor)
Selected Public Data
Source
Your Data Source
(private)
CompariSense®
Scene 4: Vicki can also create Virtual Sensors by fusioning
other data sources.
CompariSense®
When Vicki is unable to find a suited data source, she can create a virtual sensor by fusing other data sources.
Other users can also use the virtual sensors that Vicki makes public and create new virtual sensors based on that
one.
Sometimes I create a
virtual sensor to
validate my data,
when I can’t find a
suited data source.
CompariSense®
CompariSense®
Create Virtual Sensor
Not finding what you need?
CompariSense® allows you to
create virtual sensors by
combining other data sources.
Virtuel sensors are marked with
this symbol.
Traffic
Traffic Noise: 93 dB
Water Temp: 4 C
Traffic Count: 20
Traffic Count: 24
CompariSense®
Selected Public Data Source
(Virtual sensor)
Selected Public Data Source
Your Data Source (private)
Graph View
Data View
Sensor Value Time Avg. Daily
Value
QoI
Selected
Public Data
Source
(Virtual
sensor)
65 08:22 60 2
Selected
Public Data
Source
56 08:22 66 4
Your Data
Source
(private)
56 08:22 64 3
Saved Data Sources
E.g. ”Humidity Sensors”
Traffic Noise: 93 dB
Humidity Sensor: 70
Water Temp: 4 C
IoTCrawler enables the CompariSense application to find suited
data sources that the startups can use to validate their products.
Customers can also use it to document the quality of the product
that they are testing.
IoTCrawler is also capable of producing quality metrics of a given
data source, so it is transparent to other users what makes it a
relevant data source to use as validation of a different IoT
product.
IoTCrawler
Machine Monitoring Dashboard
Industrial machining on the shop floor is creating a mass of Data from
sensors during the production process.
It’s a challenge for humans to identify critical processes or anomalies on
the amount of data process data on manufacturing sites.
Powerful searching is needed to create added value from industrial process
data e.g. to detect conditions for predictive maintenance or optimize the
production process.
Scene 1: Peter is a shop floor production manager working on
continuous production improvements (KAIZEN).
Peter needs an overview on anomalies in the production to track them and implement solutions to solve.
Traditionally the anomalies are reported by production workers on Whiteboards in the production during a shift.
Machine Monitoring Dashboard
Scene 2: Peter can use mobile KAIZEN interfaces to see the
workers report everywhere.
Peter has a digital and mobile frontend to access the worker shift reports to get status information of anomalies
during a production shift.
Machine Monitoring Dashboard
Scene 3: Peter search production data linked to anomalies
Selcted Public Data Source
(Virtual sensor)
Selected Public Data Source
Your Data Source (private)
Show me the status
of cutting tools at
Machine 1 compared
to Machine 4
Machine Monitoring Dashboard
Scene 4: The results helps him to implement an optimization
on the Shop floor during his KAIZEN cycle.
The result of human reports is validated and added with digital sensor data. This will lead into changes on the shop
floor processes to be discussed with production shift leader and introduced on production.
We need to
change
maintenance
cycle for
cutting tools
Machine Monitoring Dashboard
IoT Crawler is used to search industrial process data and show
search results on mobile human interfaces as e.g. dashboards for tablets.
The data is collected and aggregated from real time machining
and stored in a search index.
IoTCrawler
Smart Energy
Energy Aggregator
Characters Page 02
SMART ENERGY
Energy Market
Scene 1: Current electricity market situation Main character: Energy market | Page 03
Only assets which have passed prequalification may
participate in flexibility trading. I need control
power in a
certain area
for balancing
the grid!
Ok, here is
my offer!
SMART ENERGY
Grid Operator
or
Energy Supplier
Power Plant
Operator
Scene 2: Future electricity market Main character: TGO| Page 03
Thanks to IoT crawler, small, not prequalified energy prosumers
can participate in flexibility trading, too.
I need control
power in a
certain area for
balancing the
grid!
Ok, here is
my offer!
Virtual Power Plant
Operator (Aggreator)
SMART ENERGY
I can also offer
energy!
Grid Operator
or
Energy Supplier
Power Plant
Operator
Scene 3: Continuous service discovery Main character: IoT crawler | Page 04
The IoT crawler continuously scans the IoT network for
potential assets to participate in flexibility trading
*crawling*
SMART ENERGY
Scene 4: Issue semantic search Main character: Energy aggregator | Page 05
The aggregator asks the IoT crawler via its semantic query interface for
suitable resources by specifying the desired power profile, offered
incentives, region where the control energy is needed and quality criteria.
• Power profile?
• Price?
• Location?
Hmm…
SMART ENERGY
Scene 5: Semantic search results Main character: IoT crawler | Page 06
The IoT crawler processes the semantic search request and queries its
context image on currently available assets matching the search criteria
and returns the ranked results to the aggregator.
1. Home_XYZ ((P=1,5kW,
t=20min),…, r=0,95)
2. PV ((P=2,25kW,
t=30min),…,r=0,80)
3. EV-Charger ((P=11kW,
t=10min),..., r=0,75…)
4. Home_ABC((P=2,5kW,
t=20min),… r=0,5)
5. …
Aha…
SMART ENERGY
Scene 6: Result selection Main character: Energy aggregator | Page 07
The aggregator picks the offers it needs to fulfill the control
power demand.
I’ll take:
• Home_XYZ (1,5kW,
20min…)
• PV (2,25kW,
30min…)
• EV-Charger (11kW,
10min…)
• …
Allright!
SMART ENERGY
Scene 7: Receiving service endpoints Main character: IoT crawler | Page 08
The IoT Crawler returns the endpoints of the selected services to the
aggregator
Here are your service
endpoints:
• http://…
• http://…
• http://…Thanks!
SMART ENERGY
Scene 8: Collecting flexibility Main character: Energy aggregator | Page 09
The aggregator requests the control power directly from the selected assets. If assets
are unavailable, the next available will be selected according to the ranking.
SMART ENERGY
Scene 9: Control energy trade Main character: Energy aggregator | Page 10
The aggregator sells cumulated control power from small
assets to the energy market.
I need control
energy!
Here is my
control energy
offer!
SMART ENERGY
Transmission grid
operator
Scene 10: Update ratings at IoT crawler Main character: Energy aggregator | Page 11
The aggregator passes its new ratings back to the context
management (via the query interface) in order to improve future
search results.
• UpdateRating(Home_
XYZ, 1)
• UpdateRating(PV, 0)
• UpdateRating(EV-
Charger, 0,5) I see…
SMART ENERGY
Unrestricted © Siemens AG 2019
2019-04-25Page 60
Now a little bit more technical….
Unrestricted © Siemens AG 2019
2019-04-25Page 61
Baseline: Service discovery in building automation and
energy systems
Context
Management
Ranking
Semantic Search IoT Discovery
BT1
BEMS
Semantic search
Rated results
Indexing Ranking
Edge
Broker
Unrestricted © Siemens AG 2019
2019-04-25Page 62
Next step: Service discovery for a Virtual Power Plant on a
swarm of assets
Semantic search
Rated results
BT1 BT1 BT1
BEMS
Semantic search
BEMS
Semantic search
Rated results
BEMS
Semantic search
Context
Management Ranking
Semantic Search IoT DiscoveryVirtual
Power Plant Indexing Ranking
Federated Broker
NGSI NGSI NGSI
. . .
NGSI

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Iotweek Iotcrawler Concept Pitches

  • 1. IoT Search Engine Concept Pitches Work created with Scenes™ by SAP AppHaus (https://experience.sap.com/designservices/scenes)
  • 2. Room Booking Currently, booking systems don’t register if a user shows up at their reservation, thus creating the illusion to other users, that the rooms are booked.This creates frustration and distrust towards the system.To compensate the distrust, students manually check every room. The students/employees etc. needs a solution that provides an overview, and instant live updates on rooms availability to gain the trust for the room booking system.
  • 3. Scene 1: Campus rooms seem to be unavailable Room Booking This room is booked Ahh! This University seriously need more rooms! This room is booked But Not used!
  • 4. Scene 2: IoTCrawler can find available rooms Hey students! Check your phone! I can tell you where all the available rooms are, even the nearest ones to minimize downtime! Room Booking This room is booked But Not used! This room is booked But Not used! This room is booked But Not used! This room is booked But Not used! Thankfully the IoTCrawler can see if rooms are being used even though they are booked!
  • 5. Scene 3: How does it do it? Room Booking The IoTCrawler crawls the IoT network at the campus and the then calculates the situation. It can tell if the rooms actually are used despite being booked & also scan unbooked rooms to see if they are actually being used. This room is booked But Not used! This room is booked But Not used! Hey students! This is your options today: • Room 265 is available in 30min. • Room 306 is not being used right now. • Room 102 with the projector is available from 13.00-14.00 • The travel time from “home” is approx. 25 min. I think we need a projector today…
  • 6. Scene 4: A solution is provided to the students Room Booking The IoTCrawler detects a booked room for the entire day, but since no one showed up and claimed it (In compliance with the rules) The students can take over the room and book it for the remaining day… *BiB BuuP* Go to room 265, its available all day! Hey guys check it out! Apparently, there is a lot of rooms! The IoT Crawler knows the way! This room is Re-booked And now soon in use!
  • 7. Together with sensors, the IoTCrawler collects information and translate them into readable content. The sensors sends information about movement in rooms, allowing the Crawler to estimate whether people are present or not. Furthermore, the Crawler checks the booking system and compile the data. This allows users to gain insight on what time of the day, that they will be most successful with obtaining rooms. IoTCrawler
  • 8. SmartConnect Smart Home environments are extremely heterogeneous, each vendor uses its own technology and data representations. Smart Home application developers are spending considerable amount of time with the integration of vendors specific APIs. This restricts the scalability with respect to supported devices and smart home systems. Ultimately Smart Home users suffer from limited number of Smart Home solutions. On a technical level it is important to address the challenge of semantic interoperability and accelerating the integration of Smart Home devices. IoTCrawler provides a promising framework for solving this challenge in the Smart Home domain.
  • 9. Tom, Tech-Savvy Smart Home User, has found the GrowSmarter Energy Awareness application, however he cannot use it. The application doesn’t support the type of sensors that he has. Scene 1: Tom often experiences problems when he is trying to connect the different sensors in his Smart Home to a new application SmartConnect Supported sensors How can I connect my sensors to GS Dashboard? Unsupported
  • 10. Scene 2: The IoTCrawler enabled functionality “SmartConnect” automatically recognizes new sensors SmartConnect IoTCrawler checks with Tom whether the devices have been correctly recognized and integrates it so that they can be accessed by application like the GS Energy Dashboard Tom, I recognized that you have three smart plugs that can measure energy consumption. Is that correct ? Yes. Exactly!
  • 11. Scene 3: Now Tom can get insights about his energy consumption … SmartConnect Cool! Now I can use GS Dashboard with my sensors to learn about my energy consumption With the help of IoTCrawler and SmartConnect, Tom use GS Energy Awareness Dashboard with his Smart Home System.
  • 12. Scene 4: …David who developed the GS Energy Awareness Application also benefits from IoTCrawler’s integration functionality. SmartConnect Wow! With IoTCrawler I can reach many more users with the same effort With the help of IoTCrawler and SmartConnect, David’s application can be used by many more users with the same effort. Without IoTCrawler With IoTCrawler and SmartConnect
  • 13. SmartConnect relies heavily on IoTCrawlers Smart Home Crawler capability. It crawls Smart Home networks, interacts with home owners, data integrators, or uses crowd sourcing for fast integration of discovered IoT devices into IoTCrawler‘s semantic Metadata Repository (MDR) based on which indices and rankings are created. Applications can thus focus on the data rather than devices and have the potential to provide interoperability with a larger amount of smart home devices. IoTCrawler
  • 14. Elderly Care Activity patterns and changes to the daily living routines can indicate changes in health and well being. Monitoring physiological and environmental data from home and analyzing trends can lead to create personalized care and intervention plans. The work requires IoT and sensory data collection, time series data analysis, machine learning and effective ways of communicating actionable information with people, their relatives, care and clinical staff. The challenge for users is compliance, acceptance and complexity of interacting with the technology.
  • 15. Anna, an elderly dementia patient, goes out and she forgets her keys. Carla, Anna’s daughter, is worried about where her mother is. Scene 1: Dementia patient going out Where am I?? Where are my keys? Elderly Care
  • 16. IoTCrawler crawls information from sensors in Anna’s house to detect any changes and collects the data. Scene 2: Crawling sensors in the home Elderly Care 11 a.m. Room 1 No one is there 11 a.m. Room 2 No one is there 10 a.m. Kitchen Making coffee Crawling Room 1 Room 2 Kitchen
  • 17. Scene 3: Checking dementia patient status Elderly Care With IoTCrawler I can realize when my mother went out and if it’s late I can call for help. I can also see when the sensors in her home needs maintenance
  • 18. Elderly Care – UI example
  • 19. IoTCrawler provides methods for extracting patterns and trends from continuous data: machine learning models to interpret the patterns and create algorithms to detect complex conditions: Personalised and privacy´aware search and discovery methods for highly sensitive data: IoTCrawler
  • 20. Smart Parking Finding a free parking spot can be frustrating, time consuming and generates pollution. At the same time it feeds-back by worsening traffic congestion. The challenge is to help users find a free parking spot that fits their duration, distance and budget constraints.
  • 21. Scene 1: Current situation in Murcia SMART PARKING Julia lives in Corvera, a 30 minute drive to Murcia, where she works. If Julia leaves later than 7:30 there are often no free parking spots in her destination area. No free parking spots! I’ll never make it!
  • 22. Scene 2: IoTCrawler-based Smart parking service SMART PARKING Julia has heard of this new app… it uses… Crawling Regulated Parking Zone info Crawling RPZ info: Expender1: Busy Expender2: Free Expender3: Free
  • 23. Scene 3: Crawling SMART PARKING The service uses the functionality of the IoTCrawler by crawling Regulated Parking Zone information (RPZ). 10:00 a.m. Sector 2 #60% Free (likelihood) 10:00 a.m. Sector 1 #90% Free (likelihood) 10:00 a.m. Sector 3 #10% Free (likelihood) Crawling Sector1 Sector2 Sector3
  • 24. Scene 4: Julia has a great morning commute. SMART PARKING With the IoT Crawler compliant app Julia’s commute will be much less stressful. The application will also readjust if traffic jams happen. There's a lot of traffic. But, I’ll make it in time.
  • 25. IoTCrawler gathers information on the different parking alternatives, indexing and ranking them according to parameters relevant to the user. When queried, it returns updated and precise information, allowing us to offer flexible and agile suggestions to the user. IoTCrawler
  • 26. Pop-up Experimentation Space The concepts are based on insights from the collaboration phase. We focused on Aarhus’ Smart City lab – our outdoor testing area for smart city solutions. In a workshop with a neighboring high-school we found out that dream of a greener Aarhus City Lab and that it might be used for sustainability experiments. Their ideas for monitoring and plants in this public space, could also be used to support biology innovation class. Through interviews and workshop with IoT startups and Smart City stakeholders, we found out that there is a need for and a better overview of the options. We build on the potential we see in easy access to flexible areas for and testing IoT experiments – for formal, informal and – by using IoTCrawler functionalities.
  • 27. Concept 3: Pop-up Experiment space Subject: Sustainable innovation & IoT solutions The innovation teacher Patrick from the local high school has planned to work with IoT over the course of 8 lessons with the students. He wants the lessons to be connected to real-life needs and environments. Tomorrows lesson starts at 9:00 at City Lab Don’t be late! Scene 1: The high-school has a need for an outdoor area for an experiment with IoT Pop-up Experimentation Space®
  • 28. Concept 3: Pop-up Experiment space The next day and the week after the students work on their IoT solutions and they setup experiments in the Pop-up experiment space. Scene 2: They use the service “Pop-up experiment space” to find an experiment space nearby. Pop-up Experimentation Space®
  • 29. Concept 3: Pop-up Experiment space The sensors are placed and activated. The monitoring system is setup online. Scene 3: The students carry out their experiments. Pop-up Experimentation Space®
  • 30. The sensor data is released for others to see and the municipality use it to know when to water else-where in Aarhus. The IoTCrawler makes it possible for the municipality and citizens to track and use external data sources. Scene 4: The data from the IoT sensors are easily available on the Pop-up experiment space platform. Pop-up Experimentation Space®
  • 31. Pop-up Experimentation Space® SubscribeJoin The IoT Garden Join Katedral School and others exploring sustainable IoT solutions… [Read more] Create a new Experiment Space Manage an existing Experiment Space Search Experiment Spaces E.g. ”IoT Garden”
  • 32. Subscribe Join The IoT Garden Join Katedral School and others in exploring how IoT Solutions can support sustainability in the cities. Join this space if you want to add your own sensors or IoT solutions – follow the rules and guidelines for experimenting in this space. You can also subscribe to the data feed from this experiment space. Experiment Dashboard Experiment Updates Suggested: Surrounding Data Testing Smart Bench Garden sensors Smart Compost Bin Experiment Space Rules • All ideas need to be approved by the City of Aarhus since this is a public space. After joining you can apply with a solution. • All solutions should be mobile or easy to remove. • The solutions may not interfere with the everyday use of the area. Create a new Experiment Space Manage an existing Experiment Space Search Experiment Spaces E.g. ”IoT Garden” Last Crawled: 2 hours ago by IoTCrawler Soil-moisture Sensor Quality Metrics Latest Value and Time Stamp Traffic Noise Quality Metrics Latest Value and Time Stamp Pop-up Experimentation Space®
  • 33. IoTCrawler crawls the geofenced area that defines the experimentation space and automatically integrates all IoT sensors and devices from users who have been allowed to be part of this particular experimentation space. A user can subscribe to the data generated in the experimentation space, which IoTCrawler delivers and monitor its quality. IoTCrawler
  • 34. CompariSense In the early stages of an IoT startup’s product development there is a need to find out if the product generates valid data by comparing it to other data sources. E.g. for parking sensors, startups could use webcams as to way to identify if a car is parked. or if you are measuring air quality there might be existing/competing products in a city that could be used to benchmark your product. The concept “CompariSense” give IoT startups and their customers an easier way to test and benchmark IoT products.
  • 35. Scene 1: Vicki runs an IoT start-up and has created a new IoT product that measures UV levels. CompariSense® Vicki needs to verify that the data her products generate is valid. Normally she would compare the data from her IoT device with data from other sensors she has made or a reference data set that a customer asks her to use.
  • 36. Scene 2: This time Vicki uses a service called CompariSense to validate her data. CompariSense® She searches for UV sensors on the CompariSense platform and a list of available UV sensors shows up. She saves them to her profile on CompariSense and starts monitoring them along with her own data to validate her product. These UV sensors are just what I need in order to test my product. CompariSense® CompariSense® UV
  • 37. Scene 3: Vicki monitors the data and sees an anomality CompariSense® Vicki can see that her own data spikes on certain times of the day compared to the other sources, so she explores the problem and identifies a solution. Hmm…. My measurements seem to be a bit off compared to the other data sources. Selected Public Data Source (Virtual sensor) Selected Public Data Source Your Data Source (private) CompariSense®
  • 38. Scene 4: Vicki can also create Virtual Sensors by fusioning other data sources. CompariSense® When Vicki is unable to find a suited data source, she can create a virtual sensor by fusing other data sources. Other users can also use the virtual sensors that Vicki makes public and create new virtual sensors based on that one. Sometimes I create a virtual sensor to validate my data, when I can’t find a suited data source. CompariSense®
  • 39. CompariSense® Create Virtual Sensor Not finding what you need? CompariSense® allows you to create virtual sensors by combining other data sources. Virtuel sensors are marked with this symbol. Traffic Traffic Noise: 93 dB Water Temp: 4 C Traffic Count: 20 Traffic Count: 24
  • 40. CompariSense® Selected Public Data Source (Virtual sensor) Selected Public Data Source Your Data Source (private) Graph View Data View Sensor Value Time Avg. Daily Value QoI Selected Public Data Source (Virtual sensor) 65 08:22 60 2 Selected Public Data Source 56 08:22 66 4 Your Data Source (private) 56 08:22 64 3 Saved Data Sources E.g. ”Humidity Sensors” Traffic Noise: 93 dB Humidity Sensor: 70 Water Temp: 4 C
  • 41. IoTCrawler enables the CompariSense application to find suited data sources that the startups can use to validate their products. Customers can also use it to document the quality of the product that they are testing. IoTCrawler is also capable of producing quality metrics of a given data source, so it is transparent to other users what makes it a relevant data source to use as validation of a different IoT product. IoTCrawler
  • 42. Machine Monitoring Dashboard Industrial machining on the shop floor is creating a mass of Data from sensors during the production process. It’s a challenge for humans to identify critical processes or anomalies on the amount of data process data on manufacturing sites. Powerful searching is needed to create added value from industrial process data e.g. to detect conditions for predictive maintenance or optimize the production process.
  • 43. Scene 1: Peter is a shop floor production manager working on continuous production improvements (KAIZEN). Peter needs an overview on anomalies in the production to track them and implement solutions to solve. Traditionally the anomalies are reported by production workers on Whiteboards in the production during a shift. Machine Monitoring Dashboard
  • 44. Scene 2: Peter can use mobile KAIZEN interfaces to see the workers report everywhere. Peter has a digital and mobile frontend to access the worker shift reports to get status information of anomalies during a production shift. Machine Monitoring Dashboard
  • 45. Scene 3: Peter search production data linked to anomalies Selcted Public Data Source (Virtual sensor) Selected Public Data Source Your Data Source (private) Show me the status of cutting tools at Machine 1 compared to Machine 4 Machine Monitoring Dashboard
  • 46. Scene 4: The results helps him to implement an optimization on the Shop floor during his KAIZEN cycle. The result of human reports is validated and added with digital sensor data. This will lead into changes on the shop floor processes to be discussed with production shift leader and introduced on production. We need to change maintenance cycle for cutting tools Machine Monitoring Dashboard
  • 47. IoT Crawler is used to search industrial process data and show search results on mobile human interfaces as e.g. dashboards for tablets. The data is collected and aggregated from real time machining and stored in a search index. IoTCrawler
  • 49. Energy Aggregator Characters Page 02 SMART ENERGY Energy Market
  • 50. Scene 1: Current electricity market situation Main character: Energy market | Page 03 Only assets which have passed prequalification may participate in flexibility trading. I need control power in a certain area for balancing the grid! Ok, here is my offer! SMART ENERGY Grid Operator or Energy Supplier Power Plant Operator
  • 51. Scene 2: Future electricity market Main character: TGO| Page 03 Thanks to IoT crawler, small, not prequalified energy prosumers can participate in flexibility trading, too. I need control power in a certain area for balancing the grid! Ok, here is my offer! Virtual Power Plant Operator (Aggreator) SMART ENERGY I can also offer energy! Grid Operator or Energy Supplier Power Plant Operator
  • 52. Scene 3: Continuous service discovery Main character: IoT crawler | Page 04 The IoT crawler continuously scans the IoT network for potential assets to participate in flexibility trading *crawling* SMART ENERGY
  • 53. Scene 4: Issue semantic search Main character: Energy aggregator | Page 05 The aggregator asks the IoT crawler via its semantic query interface for suitable resources by specifying the desired power profile, offered incentives, region where the control energy is needed and quality criteria. • Power profile? • Price? • Location? Hmm… SMART ENERGY
  • 54. Scene 5: Semantic search results Main character: IoT crawler | Page 06 The IoT crawler processes the semantic search request and queries its context image on currently available assets matching the search criteria and returns the ranked results to the aggregator. 1. Home_XYZ ((P=1,5kW, t=20min),…, r=0,95) 2. PV ((P=2,25kW, t=30min),…,r=0,80) 3. EV-Charger ((P=11kW, t=10min),..., r=0,75…) 4. Home_ABC((P=2,5kW, t=20min),… r=0,5) 5. … Aha… SMART ENERGY
  • 55. Scene 6: Result selection Main character: Energy aggregator | Page 07 The aggregator picks the offers it needs to fulfill the control power demand. I’ll take: • Home_XYZ (1,5kW, 20min…) • PV (2,25kW, 30min…) • EV-Charger (11kW, 10min…) • … Allright! SMART ENERGY
  • 56. Scene 7: Receiving service endpoints Main character: IoT crawler | Page 08 The IoT Crawler returns the endpoints of the selected services to the aggregator Here are your service endpoints: • http://… • http://… • http://…Thanks! SMART ENERGY
  • 57. Scene 8: Collecting flexibility Main character: Energy aggregator | Page 09 The aggregator requests the control power directly from the selected assets. If assets are unavailable, the next available will be selected according to the ranking. SMART ENERGY
  • 58. Scene 9: Control energy trade Main character: Energy aggregator | Page 10 The aggregator sells cumulated control power from small assets to the energy market. I need control energy! Here is my control energy offer! SMART ENERGY Transmission grid operator
  • 59. Scene 10: Update ratings at IoT crawler Main character: Energy aggregator | Page 11 The aggregator passes its new ratings back to the context management (via the query interface) in order to improve future search results. • UpdateRating(Home_ XYZ, 1) • UpdateRating(PV, 0) • UpdateRating(EV- Charger, 0,5) I see… SMART ENERGY
  • 60. Unrestricted © Siemens AG 2019 2019-04-25Page 60 Now a little bit more technical….
  • 61. Unrestricted © Siemens AG 2019 2019-04-25Page 61 Baseline: Service discovery in building automation and energy systems Context Management Ranking Semantic Search IoT Discovery BT1 BEMS Semantic search Rated results Indexing Ranking Edge Broker
  • 62. Unrestricted © Siemens AG 2019 2019-04-25Page 62 Next step: Service discovery for a Virtual Power Plant on a swarm of assets Semantic search Rated results BT1 BT1 BT1 BEMS Semantic search BEMS Semantic search Rated results BEMS Semantic search Context Management Ranking Semantic Search IoT DiscoveryVirtual Power Plant Indexing Ranking Federated Broker NGSI NGSI NGSI . . . NGSI

Hinweis der Redaktion

  1. More details. What does the crawler do?
  2. More specific details would be nice. What does the crawler do? Give real street names to the sectors.