SlideShare a Scribd company logo
1 of 11
Download to read offline
Revue de presse IoT / Data du 26/03/2017
Bonjour,
Voici la revue de presse IoT/data/energie du 26 mars 2017.
Je suis preneur d'autres artices / sources !
Bonne lecture !
1. From the Edge To the Enterprise
2. The Internet of Energy: Smart Sockets
3. Google's big data calculates US rooftop solar potential
4. Energy management: Oracle Utilities launches smart grid and IoT device
management solution in the cloud
5. Are vehicles the mobile sensor beds of the future?
From the Edge To the Enterprise
Source URL: http://www.elp.com/articles/powergrid_international/print/volume-
22/issue-3/features/from-the-edge-to-the-enterprise.html
03/20/2017
Making the case for the value of IoT
By Bradley Williams, Oracle Utilities
While we are only just beginning to understand the full impact and meaning of the Internet
of Things (IoT) for the utilities industry, the industry is already changing and transforming
because of it.
To be clear, the utility industry is not unfamiliar with the IoT. The smart grid applies IoT
technology (such as smart sensors, two-way communications and data analytics) to the
electric grid infrastructure. This enables better efficiency, improved reliability, the
integration of more renewables and distributed energy resources, reduced emissions and
more engaged and empowered customers.
Now, utilities are perfectly positioned to use this solid foundation to take advantage of IoT
as it expands, setting the stage for continued business relevance, growth and
improvement in the years ahead.
The IoT's value proposition for utilities
In coming years, the utilities industry is expected to drive exponential growth of new IoT
applications to communicate machine-to-machine to new field devices and consumer
energy technology devices at the edge of the grid. But even more important than this
ubiquitous communication is the sensor data being gathered by these machines, and the
ways in which that data can be operationalized for more efficient and proactive utility
efforts.
IoT is all about the services: transforming data from disparate devices into valued insights
and actions. Its value proposition for utilities is clear.
IoT will allow utilities to:
• Quickly translate vast quantities of sensor-based information into action
• Securely connect devices, analyze real-time and historical data and integrate to back-
end utility applications
• Enable the business to deliver innovative new services faster and with less risk
• Track crew locations and remote parts inventories to more effectively dispatch
technicians in the field
• Transform the business from the edge to the enterprise, including the control and
maintenance of new generation assets
Deploying Utility IoT
It's not necessary to take an "all-in, boil-the-ocean" approach to IoT. Instead, taking a
phased approach allows for learning and adjusting along the way.
In the first phase, the focus is on validating the business value of IoT by quickly
connecting assets and monitoring them, with the focus being purely on monitoring the
devices and reacting to events and exceptions/failures.
In the second phase, the utility's focus shifts from reactive to proactive decision-making:
analyzing the data to predict future events for proactive operational responses, identifying
energy usage patterns, etc.
In the third phase, IoT is strongly tied into enterprise processes and applications, to
optimize the back office and proactively provide an increasingly engaged customer
experience.
What does this look like, optimally? Let's look at different ways to leverage IoT
technologies to enable the vision of the future utility.
Deeper insights into asset performance management
Asset performance management is an integral tool for utilities juggling ever-increasing
operating costs with a need to reduce expenses, decrease environmental impact and
deliver more customer-centric service. Low-cost, smart field sensors are now providing
many real-time eyes all along the grid, enabling utility operators to "keep a close eye" on
assets and make decisions about asset replacement and repair before assets break
down.
There's more to it than just keeping eyes on the assets, however. The ability to aggregate
all asset data, including work history and condition rating, into a single system, balance
the importance of one factor over another, and update in real-time any condition changes
as they occur, allows the utility to make more reliable and meaningful investment and
work decisions on how to best balance compliance, reliability, safety and risk.
Why is this so important? Historically, this type of insight was based upon intuition and
subjective or observed, eyes-in-the-field assessment. In an increasingly digitized utility
environment, this type of assessment is being replaced by objective data analysis that is
by its nature more accurate, providing utilities with far more actionable insight than
before. When this analysis is automated as a core business process, it has already
demonstrated significant capacity to affect margin: proactive work has been shown to
reduce asset failure rates and drive down the cost to operate each asset, thereby
increasing revenue.
Here is a specific example to illustrate: By scheduling proactive work during normal
business hours instead of having to react to a failure with an after-hours call-out, you can
reduce costs while significantly improving reliability. With smart sensor and control
devices-many of which are IP-addressable and wireless connected-along the utility's
infrastructure, you can also add automated, real-time asset analysis to your asset
management practices. Advanced asset risk analytics can then correlate the appropriate
data from across the enterprise to provide immediate prescriptive maintenance work
requests.
Improved grid optimization with new energy resources
Electric utilities recognize the need for new distribution network technologies to
accommodate sustainable growth and customers' growing interest in grid-connected,
customer-owned distributed energy resources (DER) such as rooftop solar and on-site
energy storage. This customer-led energy evolution is driving change for utilities, too, in
terms of the way the modern distribution grid will soon need to operate. These new grid
participants want to connect with their utilities in a different manner than we have seen in
the past, and become part of the electric distribution system, rather than separate from it.
The real-time data these connected DER are also providing offer a means for utilities to
change the way they manage the grid.
IoT technologies offer utilities the ability to take a data-centric approach to distribution
management, providing a means in which to monitor, control and optimize both traditional
distribution and new, consumer energy resources. By treating each DER as an asset, and
modeling its generation output profile similarly (by aggregating the asset data, as well as
its unique attributes such as location, direction and pitch of panels, condition of use, time
of day, etc.), the utility can better forecast how and where within its service territory those
DER assets will impact the distribution grid, and use this information to improve long-term
resource planning.
Distribution grid operation can be maximized, and real-time information can reduce the
capacity for intermittency issues (from solar resources) to cause disruption or safety
problems, improve generation output profiling (thereby minimizing customer interruption
minutes), and dynamically balance consumer supply and demand of DER, thereby
alleviating utility constraint on peak load days without having to shift to extremely costly
"peaker" generation plants.
Preparing for a consumer-driven energy market
As consumer-owned in-home devices and DER continue to increase, IoT technologies will
be the foundation for an even smarter smart grid, one that can support the transactive
energy market that is already beginning to take shape. This will not happen overnight.
Some states, like New York, are leading the way in raising the foundation for this future
energy platform, and other states are just beginning that journey with smart meters,
electric vehicles and DER. But there is no question that the electric utility industry, and the
grid upon which it manages and distributes its product, is transforming.
In this transformative period, utilities have a choice: they can view the challenge to their
traditional ways of doing business as a threat, or they can turn it into a business
opportunity to improve their investment performance, lower operating costs, and provide
their customers with ways in which to participate that fit their changing expectations
about the ways they use electricity.
The transactive energy construct paves the way for this future vision, and IoT
technologies will provide the tools for utilities to effectively manage this new, dynamic
market exchange equation, balancing energy supply and demand and monitoring grid
asset health in real-time.
Taking the next steps
End-to-end grid visibility, with the ability to manage, analyze and control additional grid-
edge resources being added on an often-daily basis, will be imperative for utilities as the
work their distribution grids is being asked to do evolves. The IoT enables utilities to
create a scalable, flexible and more modular infrastructure that will be much better
equipped to face new challenges, and to quickly adapt as markets and situations change.
The Internet of Energy: Smart Sockets
Source URL: http://www.azocleantech.com/article.aspx?ArticleID=641
Written by AZoCleantech Mar 25 2017
We waste too much energy and this is a direct cause of global warming. Imagine a
fully integrated electrical system thatis safer, cleaner and sustainable. By utilising
the Internet, Smart devices, sensors and switches technologists have designed
systems that save energy in an intelligent fashion, saving the consumer money in
the process.
The Internet of things
Sometimes the simplest ideas are the best: The Internet of Things uses the existing
infrastructure of the Internet to allow devices to communicate and share data. These
devices include sensors, Smart devices, lights, motors and vehicles as well as any
compatible electronics. The advantages of such a system are increases in automation,
accuracy, efficiency and experience quality; going beyond current “machine : machine”
systems. It is estimated that the IOT will contain over 50 billion objects by 2020.
The Internet of Energy
As a subset of the IOT, the Internet of Energy (IOE) encompasses all objects involved in
provision and use of electricity from the power grid down to individual electronic devices.
The main objective of the IOE is to develop hardware, software and middleware for
seamless, secure connectivity and interoperability achieved by connecting the Internet
with the energy grids. The implementation of IoE services involves the use of multiple
components, including embedded systems, power electronics or sensors; which are an
essential part of the infrastructure dedicated to the generation and distribution energy.
The Smart Grid
Large territories have developed interconnected electrical supply systems that use the
same voltages and currents; these are most evident in large countries/continents like
USA, Brazil and the EU where the electrical grids are standardised.
The IOE makes use of millions of sensors across the grid (devices, sockets etc) and
integrated computing systems, connected using existing Internet infrastructure, allowing
the prediction of future energy requirements: The Smart Grid. This affords huge savings in
the amount of energy usage, in the form of fossil fuels and others. Encouragingly there
are currently over 500 Smart Grid projects throughout the EU.
Smart Energy Devices
Smart socket devices on the market offer basic functionality that trails behind what has
been achieved in the lab; available devices can turn off appliances, run schedules and
monitor consumption but they are not fully automated ie. they do not respond intelligently
to real time changes.
The importance of Smart devices in the IOE cannot be underestimated and researchers at
The University of Coruña have recently presented a system that monitors electrical usage
in the home and optimises consumption according to user preferences and electricity
prices.
Researchers have a produced an integrated system that uses live electricity prices,
obtained from the Internet, in order to optimise usage for the user. This system also self-
organises, using the WiFi infrastructure so that it can collect data with minimal user
intervention. All of the software is open source, allowing its modification by future
developers and uses.
The System
Sensor and actuation subsystem: This controls the sensors and actuators of the system;
responsible for collecting current data and for activating the power outlet when it receives
a request from the control subsystem.
Communications subsystem: This consists of wireless transceivers that join an auto-
configurable star topology.
Management subsystem: This provides the user with the possibility of obtaining the
current status of all modules, modifying their configuration and acting directly on them
remotely through a web interface.
Control subsystem:This oversees controlling and managing the remaining subsystems,
processing the data through the appropriate algorithms and acts as the gateway of the
network to connect to the Internet.
The Future of the IOE
It has been demonstrated that this system can be used to operate devices at optimum
times, saving energy and money (up to 70€ / year /device) by using online energy prices.
It could also be optimised according to energy availability; for example, washing
machines would be used at midday, when the electricity generated from solar panels is at
a maximum. Smart sockets, thermostats and motion detectors are well established
technologies that are integrated into the IOE in Smart Houses; these monitor all energy
used by the home and data can be analysed / modelled for specific streets or areas.
The Internet of Energy will ultimately provide a beautifully integrated system that monitors
and predicts consumption patterns. Eventually systems like the one presented here will
exist in all homes and feedback data that optimises power generation. This system will
offer high levels of participation to the user; plug and play convenience for new devices;
faster response to power outages and faults; and resilience to attack and natural
disasters. The IOE can operate on a small scale, saving the user money in the home; as
well on the grid scale, allowing more efficient electricity generation and decreasing fossil
fuel usage.
References
1. Steinbach, E., Kranz, M., Maier, W., Schweiger, F. & Alt, N. Advances in media
technology. Camera5, 247–8 (2011).
2. Blanco-Novoa, Ó., Fernández-Caramés, T., Fraga-Lamas, P. & Castedo, L. An
Electricity Price-Aware Open-Source Smart Socket for the Internet of Energy.
Sensors17, 643 (2017)
Google's big data calculates US rooftop
solar potential
Source URL: http://www.decentralized-energy.com/articles/2017/03/google-s-big-data-
calculates-us-rooftop-solar-potential.html
20/03/2017
By Tildy Bayar
Features Editor
In an application of big-data capabilities to the decentralized energy sector, a project by
Google has found that almost 80% of rooftops in the US are suitable for solar systems.
Since its inception in 2015, the company’s Project Sunroof has analyzed around 60 million
buildings in all 50 US states, determining overall that 79% have enough unshaded area to
install photovoltaic (PV)panels.
In sunnier states such as Hawaii, Arizona, Nevada and New Mexico, the analysis found
that over 90% of rooftops could support PV, while rooftops in more northerly states such
as Pennsylvania, Maine and Minnesota are only around 60% suitable.
Among cities, Houston in Texas has the most solar potential, with an estimated 18,940
GWh of rooftop solar generation potential per year. Other sunny cities such as Los
Angeles in California, Phoenix in Arizona and San Antonio in Texas follow in the rankings,
with northern and often snow-bound (yet roof-plentiful) New York City in fifth place.
[Native Advertisement]
Google said the Project Sunroof tool uses imagery from its Google Maps and Google
Earth in combination with 3D modelling and machine learning. For every building included
in the data, Project Sunroof calculates the amount of sunlight received by each portion of
its roof over the course of a year, taking into account weather patterns, the sun’s position
in the sky at different times of the year, and shade from trees and tall buildings. This
estimated sunlight is translated into energy production using industry standard models for
solar installation performance.
According to Google, if the top 10 cities reached their full rooftop solar potential, they
could produce enough energy to power eight million homes across the US.
Energy management: Oracle Utilities
launches smart grid and IoT device
management solution in the cloud
Source URL: http://www.utilityproducts.com/articles/2017/03/energy-management-
oracle-utilities-launches-smart-grid-and-iot-device-management-solution-in-the-
cloud.html
03/23/2017
Energy management: Oracle has introduced Oracle Utilities Operational Device Cloud
Service (ODCS), a new cloud offering that enables utilities to further automate the
management of their grid assets and devices, at a total lower cost of ownership.
The utilities industry is going through tremendous transformation as a result of IoT and
increasing distributed energy resources. The United States alone has more than 70 million
smart meters installed [footnote] and utilities are increasingly deploying smart field
sensors. As each smart device has its own unique requirements for maintenance,
inspection, firmware upgrades and security, utilities are struggling to manage the lifecycle
of these assets in a single, centralized way. In response to these challenges, Oracle has
unveiled a cloud-based version of its Operational Device Management Solution that
provides a scalable and future-proof way to manage IoT device operations.
Available as a new stand-alone cloud service, ODSC automates the management of
smart grid and IoT devices. When combined with Oracle Utilities Work and Asset
Management solution, it delivers a unified solution in the cloud to extend asset
performance management to smart devices at a massive scale. This complete visibility of
smart assets delivers detailed insights into each device’s location, characteristics, health,
and firmware upgrade status. In addition, utilities can extend ODCS for customer—owned
asset registration processes such as smart thermostats and solar PVs. Additionally, by
leveraging the cloud, utilities can reduce their total cost of ownership.
“We’re in front of the dramatic shifts the utilities industry is experiencing, providing new
technologies that meet the needs of our customers as they navigate this changing
landscape,” said Rodger Smith, general manager and senior vice president for Oracle
Utilities. “We’re committed to innovation, and to providing cloud solutions that make
operational excellence a reality for electric, gas and water utilities worldwide.”
The solution can be added to Oracle Utilities Work and Asset Cloud Service and Oracle
Utilities Meter Data Analytics Cloud Service or used as a stand-alone solution depending
on a utility’s requirements.
New Features in Oracle Utilities Operational Device Management Cloud Service:
• Proactively adjust, update, and repair smart grid and IoT devices as needed
• Enable significant cost savings by eliminating labor costs due to physical data collection
with automated processes
• Reduce total cost of ownership by using the most up to date IT infrastructure in the
cloud and alleviating the need to continually maintain older systems
• Find risks of device failures faster with increased visibility into the age and reliability of
each device
• Prepare for asset registration capabilities of customer-owned assets
Are vehicles the mobile sensor beds of
the future?
Source URL: http://readwrite.com/2017/03/22/are-vehicles-the-mobile-sensor-beds-of-
the-future-tl1/
Posted on March 22, 2017 in Connected Devices, Smart Cities, Transport
When people think of a car, they think of the thing that gets them from one place to the
next. Traditionally they have been just that: a tool with a single function – to get someone,
or something, from one place to another.
With the advent of new vehicle designs and the addition of new technology, that is going
to change. Just like phones have evolved over the last two decades from a single purpose
tool to one with countless functions, vehicles are now undergoing something similar.
New vehicles are being built with an increasing number of sensors. These sensors are not
only measuring how the vehicle is operating, but are starting to measure the
environmental conditions they are being used in too. Future vehicles will effectively
become mobile sensor beds, collecting data, at a granular level, across the whole planet.
The massive amounts of data being generated will be perfect for the application of
machine learning. The created algorithms will have an unprecedented level of
understanding on how the environments outside the vehicles will change over time,
Imagine a car that selected a playlist based on driving conditions. Or that knew an icy
patch was up ahead because the car that drove past that point an hour ago sensed wet
road conditions and the temperature has just dropped to the point that it will freeze.
These are just the tip of the iceberg on some of the things machine learning will bring to
vehicles on the road.
Startups are leading the charge
Current technology tends to revolve around the creation or aggregation of data with an
intended future application to machine learning. Nauto and UrbanLogiq are two startups
in this space.
Nauto is building a data set to help OEMs and other partners develop the next generation
of autonomous capability for vehicles in urban areas. However, their data set also
includes things such as road conditions and how they change over time. This could be
used, alongside machine learning, in the future to determine when and where cities
should do maintenance to optimize their budgets and road safety.
UrbanLogiq is not building a data set, but preparing governments for the arrival smart car
technology. They’re building a platform that would integrate data from systems like Nauto
with the government’s own traffic sensor data to facilitate responsive traffic light timing.
Using machine-learning, this aggregation of data will help city planners understand and
predict the evolution of their communities
This month, Google has also made a play in this space to tackle a common pain in city
driving – finding where to park. They are using the data they collect to create predictions
on where there might be free parking.
Creating an intelligent future
These technologies are just the start of how environment data collected from vehicles will
change the world. With millions of vehicles on the roads every day, they will be collecting
data everywhere and on potentially everything they come across.
A change that will probably happen in the near future is related to weather data, patterns,
and forecasts. Each vehicle could be constantly collecting temperature, pressure, and
potentially even wind speed and uploading all that data to a centralized system. With
millions of vehicles on the road, you have a geographic data set that is extremely granular
allowing strong predictions on how the weather will change over time. With machine
vision added to these vehicles, the possibilities increase exponentially, allowing for exact
positioning of lightning, and high-resolution, three-dimensional modeling of storm fronts.
Once you have strong weather predictions you can merge the data set with supply chain
data. This will allow companies to optimize their supply chain and inventory based on
future weather. The concept of shelves being out of stock due to weather or a
manufacturing bottleneck due to parts being unexpectedly delayed will become a thing of
the past. Companies will be able to leverage theenvironmentaldata coming off vehicles to
allow them to optimize their operations around future weather.
Another situation you will see is machine learning driven advice on when to schedule
events. You might be able to get a warning that by scheduling an event at one time, the
weather coupled with traffic will make it take an hour to get there. However, if you
schedule it an hour earlier, it may only take 15 minutes.
Environmental sensors could even be merged with sensors monitoring the driver or
passengers in the vehicle. Knowledge of what conditions make a driver feel stressed or
relaxed could be used to determine when they should drive or be driven for them to feel
best.
We can look forward to a future where our vehicles will understand the environments they
will be operating in and how that knowledge will be used to optimize our lives.
Allowing vehicles to understand the environment
Rethinking what a vehicle is. Vehicles transitioning from simply a transportation tool to a
series of sensors that travel across the world. These sensors could pick up changing road
conditions or weather patterns. These large new data sets can then be used by
governments (road repairs), insurance, or routing purposes and will allow people to make
the best data-driven decisions.
This article is part of our connected cars series. You can download a high-resolution
version of the landscape featuring 250 companies here.

More Related Content

What's hot

Cognizant Cloud for Utilities
Cognizant Cloud for UtilitiesCognizant Cloud for Utilities
Cognizant Cloud for UtilitiesSteve Lennon
 
IoT Enabled Smart Grid
IoT Enabled Smart GridIoT Enabled Smart Grid
IoT Enabled Smart Gridijsrd.com
 
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...IBM Internet of Things
 
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...Indigo Advisory Group
 
1 Smart Meter Presentation
1 Smart Meter Presentation1 Smart Meter Presentation
1 Smart Meter Presentationneumond
 
Designing for Manufacturing's 'Internet of Things'
Designing for Manufacturing's 'Internet of Things'Designing for Manufacturing's 'Internet of Things'
Designing for Manufacturing's 'Internet of Things'Cognizant
 
Optimise Buildings with AI
Optimise Buildings with AIOptimise Buildings with AI
Optimise Buildings with AIBrad Middleton
 
Managing the Energy Information Grid - Digital Strategies for Utilities
Managing the Energy Information Grid - Digital Strategies for UtilitiesManaging the Energy Information Grid - Digital Strategies for Utilities
Managing the Energy Information Grid - Digital Strategies for UtilitiesIndigo Advisory Group
 
UtiliSME - Utility Strategy - Indigo Advisory Group
UtiliSME - Utility Strategy - Indigo Advisory GroupUtiliSME - Utility Strategy - Indigo Advisory Group
UtiliSME - Utility Strategy - Indigo Advisory GroupIndigo Advisory Group
 
Blue Pillar Dell World 2016 Energy IoT presentation
Blue Pillar Dell World 2016 Energy IoT presentationBlue Pillar Dell World 2016 Energy IoT presentation
Blue Pillar Dell World 2016 Energy IoT presentationkimgetgen
 
Modeling the Grid for De-Centralized Energy
Modeling the Grid for De-Centralized EnergyModeling the Grid for De-Centralized Energy
Modeling the Grid for De-Centralized EnergyTon De Vries
 
Digital Transformation in the Lab
Digital Transformation in the LabDigital Transformation in the Lab
Digital Transformation in the Labaccenture
 
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)ideaport
 
IoT for the energy sector
IoT for the energy sectorIoT for the energy sector
IoT for the energy sectorIET India
 
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_Oct
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_OctCompegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_Oct
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_OctCOMPEGENCE
 
Indigo Capability Primer - Transformation Tools for Utilities
Indigo Capability Primer - Transformation Tools for Utilities Indigo Capability Primer - Transformation Tools for Utilities
Indigo Capability Primer - Transformation Tools for Utilities Indigo Advisory Group
 
Monet, an IoT Energy Management Platform based on MongoDB
Monet, an IoT Energy Management Platform based on MongoDBMonet, an IoT Energy Management Platform based on MongoDB
Monet, an IoT Energy Management Platform based on MongoDBSam_Francis
 
UtiliAPP - Utility Analytics - Indigo Advisory Group
UtiliAPP  - Utility Analytics - Indigo Advisory GroupUtiliAPP  - Utility Analytics - Indigo Advisory Group
UtiliAPP - Utility Analytics - Indigo Advisory GroupIndigo Advisory Group
 

What's hot (20)

Smarter planet: Energy and Utilities
Smarter planet: Energy and UtilitiesSmarter planet: Energy and Utilities
Smarter planet: Energy and Utilities
 
Cognizant Cloud for Utilities
Cognizant Cloud for UtilitiesCognizant Cloud for Utilities
Cognizant Cloud for Utilities
 
IoT Enabled Smart Grid
IoT Enabled Smart GridIoT Enabled Smart Grid
IoT Enabled Smart Grid
 
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...
Regulatory Reality Check: Improve trust, compliance and visibility with IoT a...
 
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...
Strategies to Monetize Energy Data - How Utilities Can Increase Their 'Earnin...
 
1 Smart Meter Presentation
1 Smart Meter Presentation1 Smart Meter Presentation
1 Smart Meter Presentation
 
Designing for Manufacturing's 'Internet of Things'
Designing for Manufacturing's 'Internet of Things'Designing for Manufacturing's 'Internet of Things'
Designing for Manufacturing's 'Internet of Things'
 
Optimise Buildings with AI
Optimise Buildings with AIOptimise Buildings with AI
Optimise Buildings with AI
 
Managing the Energy Information Grid - Digital Strategies for Utilities
Managing the Energy Information Grid - Digital Strategies for UtilitiesManaging the Energy Information Grid - Digital Strategies for Utilities
Managing the Energy Information Grid - Digital Strategies for Utilities
 
UtiliSME - Utility Strategy - Indigo Advisory Group
UtiliSME - Utility Strategy - Indigo Advisory GroupUtiliSME - Utility Strategy - Indigo Advisory Group
UtiliSME - Utility Strategy - Indigo Advisory Group
 
Blue Pillar Dell World 2016 Energy IoT presentation
Blue Pillar Dell World 2016 Energy IoT presentationBlue Pillar Dell World 2016 Energy IoT presentation
Blue Pillar Dell World 2016 Energy IoT presentation
 
Modeling the Grid for De-Centralized Energy
Modeling the Grid for De-Centralized EnergyModeling the Grid for De-Centralized Energy
Modeling the Grid for De-Centralized Energy
 
Digital Transformation in the Lab
Digital Transformation in the LabDigital Transformation in the Lab
Digital Transformation in the Lab
 
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)
Enerji Sektöründe Endüstriyel IoT Uygulamaları - Şahin Çağlayan (Reengen)
 
IoT for the energy sector
IoT for the energy sectorIoT for the energy sector
IoT for the energy sector
 
6 iot cases
6 iot cases6 iot cases
6 iot cases
 
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_Oct
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_OctCompegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_Oct
Compegence: Dr. Abhinanda Sarkar - Energy Analytics_IISC_2012_Oct
 
Indigo Capability Primer - Transformation Tools for Utilities
Indigo Capability Primer - Transformation Tools for Utilities Indigo Capability Primer - Transformation Tools for Utilities
Indigo Capability Primer - Transformation Tools for Utilities
 
Monet, an IoT Energy Management Platform based on MongoDB
Monet, an IoT Energy Management Platform based on MongoDBMonet, an IoT Energy Management Platform based on MongoDB
Monet, an IoT Energy Management Platform based on MongoDB
 
UtiliAPP - Utility Analytics - Indigo Advisory Group
UtiliAPP  - Utility Analytics - Indigo Advisory GroupUtiliAPP  - Utility Analytics - Indigo Advisory Group
UtiliAPP - Utility Analytics - Indigo Advisory Group
 

Viewers also liked

Plaquette Fibrea
Plaquette FibreaPlaquette Fibrea
Plaquette FibreaSOREA
 
11 flowers gifts which are perfect for allergy sufferers
11 flowers gifts which are perfect for allergy sufferers11 flowers gifts which are perfect for allergy sufferers
11 flowers gifts which are perfect for allergy sufferersCeline Wilson
 
Dementia: An Overview
Dementia: An OverviewDementia: An Overview
Dementia: An OverviewIrene Ryan
 
Prise en charge du lymphoedème en hospitalisation complète
Prise en charge du lymphoedème en hospitalisation complètePrise en charge du lymphoedème en hospitalisation complète
Prise en charge du lymphoedème en hospitalisation complèteMaxime Blanc-Fontes
 
Forum IA BX mars 2016 - Blade Runner
Forum IA BX mars 2016 - Blade RunnerForum IA BX mars 2016 - Blade Runner
Forum IA BX mars 2016 - Blade RunnerArmelle Gilliard
 
SP.Matveev.IComp.Cover.AUG2016
SP.Matveev.IComp.Cover.AUG2016SP.Matveev.IComp.Cover.AUG2016
SP.Matveev.IComp.Cover.AUG2016Alex Matveev
 
Pharmaceutical microbiology west coast
Pharmaceutical microbiology west coastPharmaceutical microbiology west coast
Pharmaceutical microbiology west coastAlia Malick
 
Secret encoder ring
Secret encoder ringSecret encoder ring
Secret encoder ringToby Jaffey
 
Qgis tutorial 01
Qgis tutorial 01Qgis tutorial 01
Qgis tutorial 01O Fukuoka
 
تعليم Css
تعليم Cssتعليم Css
تعليم CssFataho Ali
 

Viewers also liked (15)

Startup Pitch Decks
Startup Pitch DecksStartup Pitch Decks
Startup Pitch Decks
 
Plaquette Fibrea
Plaquette FibreaPlaquette Fibrea
Plaquette Fibrea
 
11 flowers gifts which are perfect for allergy sufferers
11 flowers gifts which are perfect for allergy sufferers11 flowers gifts which are perfect for allergy sufferers
11 flowers gifts which are perfect for allergy sufferers
 
Dementia: An Overview
Dementia: An OverviewDementia: An Overview
Dementia: An Overview
 
Prise en charge du lymphoedème en hospitalisation complète
Prise en charge du lymphoedème en hospitalisation complètePrise en charge du lymphoedème en hospitalisation complète
Prise en charge du lymphoedème en hospitalisation complète
 
Forum IA BX mars 2016 - Blade Runner
Forum IA BX mars 2016 - Blade RunnerForum IA BX mars 2016 - Blade Runner
Forum IA BX mars 2016 - Blade Runner
 
SP.Matveev.IComp.Cover.AUG2016
SP.Matveev.IComp.Cover.AUG2016SP.Matveev.IComp.Cover.AUG2016
SP.Matveev.IComp.Cover.AUG2016
 
Pharmaceutical microbiology west coast
Pharmaceutical microbiology west coastPharmaceutical microbiology west coast
Pharmaceutical microbiology west coast
 
Secret encoder ring
Secret encoder ringSecret encoder ring
Secret encoder ring
 
The Crazy Cuban's Secret
The  Crazy Cuban's   SecretThe  Crazy Cuban's   Secret
The Crazy Cuban's Secret
 
Zooth
ZoothZooth
Zooth
 
Зерна пам’яті
Зерна пам’ятіЗерна пам’яті
Зерна пам’яті
 
Escenes Locals 2017
Escenes Locals 2017Escenes Locals 2017
Escenes Locals 2017
 
Qgis tutorial 01
Qgis tutorial 01Qgis tutorial 01
Qgis tutorial 01
 
تعليم Css
تعليم Cssتعليم Css
تعليم Css
 

Similar to Revue de presse IoT / Data du 26/03/2017

Supporting the Smart Grid with IMDBS
Supporting the Smart Grid with IMDBSSupporting the Smart Grid with IMDBS
Supporting the Smart Grid with IMDBSStephen Dillon
 
Zpryme Report on Asset Monitoring
Zpryme Report on Asset MonitoringZpryme Report on Asset Monitoring
Zpryme Report on Asset MonitoringPaula Smith
 
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...Cognizant
 
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...IJERA Editor
 
IRJET - IoT based Energy Monitoring System for Energy Conservation
IRJET -  	  IoT based Energy Monitoring System for Energy ConservationIRJET -  	  IoT based Energy Monitoring System for Energy Conservation
IRJET - IoT based Energy Monitoring System for Energy ConservationIRJET Journal
 
How the Convergence of IT and OT Enables Smart Grid Development
How the Convergence of IT and OT Enables Smart Grid DevelopmentHow the Convergence of IT and OT Enables Smart Grid Development
How the Convergence of IT and OT Enables Smart Grid DevelopmentSchneider Electric
 
Whitepaper: Increasing Market Access with Satellite IOT
Whitepaper: Increasing Market Access with Satellite IOTWhitepaper: Increasing Market Access with Satellite IOT
Whitepaper: Increasing Market Access with Satellite IOTST Engineering iDirect
 
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-Computing
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-ComputingRedefining-Smart-Grid-Architectural-Thinking-Using-Stream-Computing
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-ComputingAjoy Kumar
 
Implementing Oracle Utility-Meter Data Management For Power Consumption
Implementing Oracle Utility-Meter Data Management For Power ConsumptionImplementing Oracle Utility-Meter Data Management For Power Consumption
Implementing Oracle Utility-Meter Data Management For Power ConsumptionIJERDJOURNAL
 
IRJET- Smart Building Automation using Internet of Things
IRJET- Smart Building Automation using Internet of ThingsIRJET- Smart Building Automation using Internet of Things
IRJET- Smart Building Automation using Internet of ThingsIRJET Journal
 
Top 10 digital trends for power and utilities
Top 10 digital trends for power and utilities Top 10 digital trends for power and utilities
Top 10 digital trends for power and utilities Olivia Falkner-Lee
 
Developing Smart Meters with IoT Technology.pdf
Developing Smart Meters with IoT Technology.pdfDeveloping Smart Meters with IoT Technology.pdf
Developing Smart Meters with IoT Technology.pdfBT Techsoft Pvt. Ltd
 
IoT in Electrical Engineering, Energy Management
IoT in Electrical Engineering, Energy ManagementIoT in Electrical Engineering, Energy Management
IoT in Electrical Engineering, Energy ManagementHadi Vatankhah Ghadim
 
IRJET- Review on Design of Residential IoT based Smart Energy Meters
IRJET- Review on Design of Residential IoT based Smart Energy MetersIRJET- Review on Design of Residential IoT based Smart Energy Meters
IRJET- Review on Design of Residential IoT based Smart Energy MetersIRJET Journal
 
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...Leonardo
 
Reaping the Benefits of the Internet of Things
Reaping the Benefits of the Internet of ThingsReaping the Benefits of the Internet of Things
Reaping the Benefits of the Internet of ThingsCognizant
 
Assessing the Business Value of SDN Datacenter Security Solutions
Assessing the Business Value of SDN Datacenter Security SolutionsAssessing the Business Value of SDN Datacenter Security Solutions
Assessing the Business Value of SDN Datacenter Security Solutionsxband
 
Behavioral dynamics intelen white R&D Paper
Behavioral dynamics intelen white R&D PaperBehavioral dynamics intelen white R&D Paper
Behavioral dynamics intelen white R&D PaperVassilis Nikolopoulos
 

Similar to Revue de presse IoT / Data du 26/03/2017 (20)

Supporting the Smart Grid with IMDBS
Supporting the Smart Grid with IMDBSSupporting the Smart Grid with IMDBS
Supporting the Smart Grid with IMDBS
 
Zpryme Report on Asset Monitoring
Zpryme Report on Asset MonitoringZpryme Report on Asset Monitoring
Zpryme Report on Asset Monitoring
 
On the Path to a Smarter World
On the Path to a Smarter WorldOn the Path to a Smarter World
On the Path to a Smarter World
 
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...
Beyond Brick and Mortar: Advanced Technology Platforms and Processes Power Sm...
 
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...
Vision and Strategy for India’s Electricity Metering Infrastructure of the fu...
 
IRJET - IoT based Energy Monitoring System for Energy Conservation
IRJET -  	  IoT based Energy Monitoring System for Energy ConservationIRJET -  	  IoT based Energy Monitoring System for Energy Conservation
IRJET - IoT based Energy Monitoring System for Energy Conservation
 
How the Convergence of IT and OT Enables Smart Grid Development
How the Convergence of IT and OT Enables Smart Grid DevelopmentHow the Convergence of IT and OT Enables Smart Grid Development
How the Convergence of IT and OT Enables Smart Grid Development
 
Whitepaper: Increasing Market Access with Satellite IOT
Whitepaper: Increasing Market Access with Satellite IOTWhitepaper: Increasing Market Access with Satellite IOT
Whitepaper: Increasing Market Access with Satellite IOT
 
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-Computing
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-ComputingRedefining-Smart-Grid-Architectural-Thinking-Using-Stream-Computing
Redefining-Smart-Grid-Architectural-Thinking-Using-Stream-Computing
 
Implementing Oracle Utility-Meter Data Management For Power Consumption
Implementing Oracle Utility-Meter Data Management For Power ConsumptionImplementing Oracle Utility-Meter Data Management For Power Consumption
Implementing Oracle Utility-Meter Data Management For Power Consumption
 
IRJET- Smart Building Automation using Internet of Things
IRJET- Smart Building Automation using Internet of ThingsIRJET- Smart Building Automation using Internet of Things
IRJET- Smart Building Automation using Internet of Things
 
Top 10 digital trends for power and utilities
Top 10 digital trends for power and utilities Top 10 digital trends for power and utilities
Top 10 digital trends for power and utilities
 
Developing Smart Meters with IoT Technology.pdf
Developing Smart Meters with IoT Technology.pdfDeveloping Smart Meters with IoT Technology.pdf
Developing Smart Meters with IoT Technology.pdf
 
IoT in Electrical Engineering, Energy Management
IoT in Electrical Engineering, Energy ManagementIoT in Electrical Engineering, Energy Management
IoT in Electrical Engineering, Energy Management
 
IRJET- Review on Design of Residential IoT based Smart Energy Meters
IRJET- Review on Design of Residential IoT based Smart Energy MetersIRJET- Review on Design of Residential IoT based Smart Energy Meters
IRJET- Review on Design of Residential IoT based Smart Energy Meters
 
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...
Smart Efficient and Secure, the new normal- Selex ES seminar at Paris Air Sho...
 
Smart Grid Deployment Experience and Utility Case Studies
Smart Grid Deployment Experience and Utility Case StudiesSmart Grid Deployment Experience and Utility Case Studies
Smart Grid Deployment Experience and Utility Case Studies
 
Reaping the Benefits of the Internet of Things
Reaping the Benefits of the Internet of ThingsReaping the Benefits of the Internet of Things
Reaping the Benefits of the Internet of Things
 
Assessing the Business Value of SDN Datacenter Security Solutions
Assessing the Business Value of SDN Datacenter Security SolutionsAssessing the Business Value of SDN Datacenter Security Solutions
Assessing the Business Value of SDN Datacenter Security Solutions
 
Behavioral dynamics intelen white R&D Paper
Behavioral dynamics intelen white R&D PaperBehavioral dynamics intelen white R&D Paper
Behavioral dynamics intelen white R&D Paper
 

More from Romain Bochet

Revue de presse IoT / Data / Energie du 02/04/2017
Revue de presse IoT / Data / Energie du 02/04/2017Revue de presse IoT / Data / Energie du 02/04/2017
Revue de presse IoT / Data / Energie du 02/04/2017Romain Bochet
 
Revue de presse IoT / Data du 19/03/2017
Revue de presse IoT / Data du 19/03/2017Revue de presse IoT / Data du 19/03/2017
Revue de presse IoT / Data du 19/03/2017Romain Bochet
 
Revue de presse IoT / Data du 13/03/2017
Revue de presse IoT / Data du 13/03/2017Revue de presse IoT / Data du 13/03/2017
Revue de presse IoT / Data du 13/03/2017Romain Bochet
 
Revue de presse IoT / Data du 04/03/2017
Revue de presse IoT / Data du 04/03/2017Revue de presse IoT / Data du 04/03/2017
Revue de presse IoT / Data du 04/03/2017Romain Bochet
 
Revue de presse IoT / Data du 26/02/2017
Revue de presse IoT / Data du 26/02/2017Revue de presse IoT / Data du 26/02/2017
Revue de presse IoT / Data du 26/02/2017Romain Bochet
 
Revue de presse IoT / Data du 04/02/2017
Revue de presse IoT / Data du 04/02/2017Revue de presse IoT / Data du 04/02/2017
Revue de presse IoT / Data du 04/02/2017Romain Bochet
 
Revue de presse IoT / Data du 28/01/2017
Revue de presse IoT / Data du 28/01/2017Revue de presse IoT / Data du 28/01/2017
Revue de presse IoT / Data du 28/01/2017Romain Bochet
 
Revue de presse IoT / Data du 22/01/2017
Revue de presse IoT / Data du 22/01/2017Revue de presse IoT / Data du 22/01/2017
Revue de presse IoT / Data du 22/01/2017Romain Bochet
 
Revue de presse IoT / Data du 15/01/2017
Revue de presse IoT / Data du 15/01/2017Revue de presse IoT / Data du 15/01/2017
Revue de presse IoT / Data du 15/01/2017Romain Bochet
 
Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Romain Bochet
 
Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Romain Bochet
 
Revue de presse IoT / Data du 01/01/2017
Revue de presse IoT / Data du 01/01/2017Revue de presse IoT / Data du 01/01/2017
Revue de presse IoT / Data du 01/01/2017Romain Bochet
 
Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Romain Bochet
 
Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Romain Bochet
 
Revue de presse IoT / Data du 17/12/2016
Revue de presse IoT / Data du 17/12/2016Revue de presse IoT / Data du 17/12/2016
Revue de presse IoT / Data du 17/12/2016Romain Bochet
 
Revue de presse IoT / Data du 01/12/2016
Revue de presse IoT / Data du 01/12/2016Revue de presse IoT / Data du 01/12/2016
Revue de presse IoT / Data du 01/12/2016Romain Bochet
 
Revue de presse IOT/ data du 03/12/2016
Revue de presse IOT/ data du 03/12/2016Revue de presse IOT/ data du 03/12/2016
Revue de presse IOT/ data du 03/12/2016Romain Bochet
 
Usage based security Framework for Collaborative Computing Systems
Usage based security Framework for Collaborative Computing SystemsUsage based security Framework for Collaborative Computing Systems
Usage based security Framework for Collaborative Computing SystemsRomain Bochet
 

More from Romain Bochet (19)

Revue de presse IoT / Data / Energie du 02/04/2017
Revue de presse IoT / Data / Energie du 02/04/2017Revue de presse IoT / Data / Energie du 02/04/2017
Revue de presse IoT / Data / Energie du 02/04/2017
 
Revue de presse IoT / Data du 19/03/2017
Revue de presse IoT / Data du 19/03/2017Revue de presse IoT / Data du 19/03/2017
Revue de presse IoT / Data du 19/03/2017
 
Revue de presse IoT / Data du 13/03/2017
Revue de presse IoT / Data du 13/03/2017Revue de presse IoT / Data du 13/03/2017
Revue de presse IoT / Data du 13/03/2017
 
Revue de presse IoT / Data du 04/03/2017
Revue de presse IoT / Data du 04/03/2017Revue de presse IoT / Data du 04/03/2017
Revue de presse IoT / Data du 04/03/2017
 
Revue de presse IoT / Data du 26/02/2017
Revue de presse IoT / Data du 26/02/2017Revue de presse IoT / Data du 26/02/2017
Revue de presse IoT / Data du 26/02/2017
 
Revue de presse IoT / Data du 04/02/2017
Revue de presse IoT / Data du 04/02/2017Revue de presse IoT / Data du 04/02/2017
Revue de presse IoT / Data du 04/02/2017
 
Revue de presse IoT / Data du 28/01/2017
Revue de presse IoT / Data du 28/01/2017Revue de presse IoT / Data du 28/01/2017
Revue de presse IoT / Data du 28/01/2017
 
Revue de presse IoT / Data du 22/01/2017
Revue de presse IoT / Data du 22/01/2017Revue de presse IoT / Data du 22/01/2017
Revue de presse IoT / Data du 22/01/2017
 
Revue de presse IoT / Data du 15/01/2017
Revue de presse IoT / Data du 15/01/2017Revue de presse IoT / Data du 15/01/2017
Revue de presse IoT / Data du 15/01/2017
 
Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017
 
Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017Revue de presse IoT / Data du 08/01/2017
Revue de presse IoT / Data du 08/01/2017
 
Revue de presse IoT / Data du 01/01/2017
Revue de presse IoT / Data du 01/01/2017Revue de presse IoT / Data du 01/01/2017
Revue de presse IoT / Data du 01/01/2017
 
Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016
 
Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016Revue de presse IoT / Data du 24/12/2016
Revue de presse IoT / Data du 24/12/2016
 
Revue de presse IoT / Data du 17/12/2016
Revue de presse IoT / Data du 17/12/2016Revue de presse IoT / Data du 17/12/2016
Revue de presse IoT / Data du 17/12/2016
 
Revue de presse IoT / Data du 01/12/2016
Revue de presse IoT / Data du 01/12/2016Revue de presse IoT / Data du 01/12/2016
Revue de presse IoT / Data du 01/12/2016
 
Revue de presse IOT/ data du 03/12/2016
Revue de presse IOT/ data du 03/12/2016Revue de presse IOT/ data du 03/12/2016
Revue de presse IOT/ data du 03/12/2016
 
Big data
Big dataBig data
Big data
 
Usage based security Framework for Collaborative Computing Systems
Usage based security Framework for Collaborative Computing SystemsUsage based security Framework for Collaborative Computing Systems
Usage based security Framework for Collaborative Computing Systems
 

Recently uploaded

PKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPramod Kumar Srivastava
 
DBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfDBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfJohn Sterrett
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样vhwb25kk
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectBoston Institute of Analytics
 
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptdokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptSonatrach
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfchwongval
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...Boston Institute of Analytics
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanMYRABACSAFRA2
 
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSINGmarianagonzalez07
 
20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdfHuman37
 
Customer Service Analytics - Make Sense of All Your Data.pptx
Customer Service Analytics - Make Sense of All Your Data.pptxCustomer Service Analytics - Make Sense of All Your Data.pptx
Customer Service Analytics - Make Sense of All Your Data.pptxEmmanuel Dauda
 
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degreeyuu sss
 
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档208367051
 
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...dajasot375
 
Defining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryDefining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryJeremy Anderson
 
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Jack DiGiovanna
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPTBoston Institute of Analytics
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsVICTOR MAESTRE RAMIREZ
 

Recently uploaded (20)

PKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptx
 
DBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdfDBA Basics: Getting Started with Performance Tuning.pdf
DBA Basics: Getting Started with Performance Tuning.pdf
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis Project
 
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptdokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdf
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
 
Call Girls in Saket 99530🔝 56974 Escort Service
Call Girls in Saket 99530🔝 56974 Escort ServiceCall Girls in Saket 99530🔝 56974 Escort Service
Call Girls in Saket 99530🔝 56974 Escort Service
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population Mean
 
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
 
Deep Generative Learning for All - The Gen AI Hype (Spring 2024)
Deep Generative Learning for All - The Gen AI Hype (Spring 2024)Deep Generative Learning for All - The Gen AI Hype (Spring 2024)
Deep Generative Learning for All - The Gen AI Hype (Spring 2024)
 
20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf
 
Customer Service Analytics - Make Sense of All Your Data.pptx
Customer Service Analytics - Make Sense of All Your Data.pptxCustomer Service Analytics - Make Sense of All Your Data.pptx
Customer Service Analytics - Make Sense of All Your Data.pptx
 
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲中央昆士兰大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
 
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
原版1:1定制南十字星大学毕业证(SCU毕业证)#文凭成绩单#真实留信学历认证永久存档
 
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...
Indian Call Girls in Abu Dhabi O5286O24O8 Call Girls in Abu Dhabi By Independ...
 
Defining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryDefining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data Story
 
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business Professionals
 

Revue de presse IoT / Data du 26/03/2017

  • 1. Revue de presse IoT / Data du 26/03/2017 Bonjour, Voici la revue de presse IoT/data/energie du 26 mars 2017. Je suis preneur d'autres artices / sources ! Bonne lecture ! 1. From the Edge To the Enterprise 2. The Internet of Energy: Smart Sockets 3. Google's big data calculates US rooftop solar potential 4. Energy management: Oracle Utilities launches smart grid and IoT device management solution in the cloud 5. Are vehicles the mobile sensor beds of the future? From the Edge To the Enterprise Source URL: http://www.elp.com/articles/powergrid_international/print/volume- 22/issue-3/features/from-the-edge-to-the-enterprise.html 03/20/2017 Making the case for the value of IoT By Bradley Williams, Oracle Utilities While we are only just beginning to understand the full impact and meaning of the Internet of Things (IoT) for the utilities industry, the industry is already changing and transforming because of it. To be clear, the utility industry is not unfamiliar with the IoT. The smart grid applies IoT technology (such as smart sensors, two-way communications and data analytics) to the electric grid infrastructure. This enables better efficiency, improved reliability, the integration of more renewables and distributed energy resources, reduced emissions and more engaged and empowered customers. Now, utilities are perfectly positioned to use this solid foundation to take advantage of IoT as it expands, setting the stage for continued business relevance, growth and improvement in the years ahead. The IoT's value proposition for utilities In coming years, the utilities industry is expected to drive exponential growth of new IoT
  • 2. applications to communicate machine-to-machine to new field devices and consumer energy technology devices at the edge of the grid. But even more important than this ubiquitous communication is the sensor data being gathered by these machines, and the ways in which that data can be operationalized for more efficient and proactive utility efforts. IoT is all about the services: transforming data from disparate devices into valued insights and actions. Its value proposition for utilities is clear. IoT will allow utilities to: • Quickly translate vast quantities of sensor-based information into action • Securely connect devices, analyze real-time and historical data and integrate to back- end utility applications • Enable the business to deliver innovative new services faster and with less risk • Track crew locations and remote parts inventories to more effectively dispatch technicians in the field • Transform the business from the edge to the enterprise, including the control and maintenance of new generation assets Deploying Utility IoT It's not necessary to take an "all-in, boil-the-ocean" approach to IoT. Instead, taking a phased approach allows for learning and adjusting along the way. In the first phase, the focus is on validating the business value of IoT by quickly connecting assets and monitoring them, with the focus being purely on monitoring the devices and reacting to events and exceptions/failures. In the second phase, the utility's focus shifts from reactive to proactive decision-making: analyzing the data to predict future events for proactive operational responses, identifying energy usage patterns, etc. In the third phase, IoT is strongly tied into enterprise processes and applications, to optimize the back office and proactively provide an increasingly engaged customer experience. What does this look like, optimally? Let's look at different ways to leverage IoT technologies to enable the vision of the future utility. Deeper insights into asset performance management Asset performance management is an integral tool for utilities juggling ever-increasing operating costs with a need to reduce expenses, decrease environmental impact and deliver more customer-centric service. Low-cost, smart field sensors are now providing many real-time eyes all along the grid, enabling utility operators to "keep a close eye" on assets and make decisions about asset replacement and repair before assets break
  • 3. down. There's more to it than just keeping eyes on the assets, however. The ability to aggregate all asset data, including work history and condition rating, into a single system, balance the importance of one factor over another, and update in real-time any condition changes as they occur, allows the utility to make more reliable and meaningful investment and work decisions on how to best balance compliance, reliability, safety and risk. Why is this so important? Historically, this type of insight was based upon intuition and subjective or observed, eyes-in-the-field assessment. In an increasingly digitized utility environment, this type of assessment is being replaced by objective data analysis that is by its nature more accurate, providing utilities with far more actionable insight than before. When this analysis is automated as a core business process, it has already demonstrated significant capacity to affect margin: proactive work has been shown to reduce asset failure rates and drive down the cost to operate each asset, thereby increasing revenue. Here is a specific example to illustrate: By scheduling proactive work during normal business hours instead of having to react to a failure with an after-hours call-out, you can reduce costs while significantly improving reliability. With smart sensor and control devices-many of which are IP-addressable and wireless connected-along the utility's infrastructure, you can also add automated, real-time asset analysis to your asset management practices. Advanced asset risk analytics can then correlate the appropriate data from across the enterprise to provide immediate prescriptive maintenance work requests. Improved grid optimization with new energy resources Electric utilities recognize the need for new distribution network technologies to accommodate sustainable growth and customers' growing interest in grid-connected, customer-owned distributed energy resources (DER) such as rooftop solar and on-site energy storage. This customer-led energy evolution is driving change for utilities, too, in terms of the way the modern distribution grid will soon need to operate. These new grid participants want to connect with their utilities in a different manner than we have seen in the past, and become part of the electric distribution system, rather than separate from it. The real-time data these connected DER are also providing offer a means for utilities to change the way they manage the grid. IoT technologies offer utilities the ability to take a data-centric approach to distribution management, providing a means in which to monitor, control and optimize both traditional distribution and new, consumer energy resources. By treating each DER as an asset, and modeling its generation output profile similarly (by aggregating the asset data, as well as its unique attributes such as location, direction and pitch of panels, condition of use, time of day, etc.), the utility can better forecast how and where within its service territory those DER assets will impact the distribution grid, and use this information to improve long-term resource planning. Distribution grid operation can be maximized, and real-time information can reduce the capacity for intermittency issues (from solar resources) to cause disruption or safety problems, improve generation output profiling (thereby minimizing customer interruption minutes), and dynamically balance consumer supply and demand of DER, thereby
  • 4. alleviating utility constraint on peak load days without having to shift to extremely costly "peaker" generation plants. Preparing for a consumer-driven energy market As consumer-owned in-home devices and DER continue to increase, IoT technologies will be the foundation for an even smarter smart grid, one that can support the transactive energy market that is already beginning to take shape. This will not happen overnight. Some states, like New York, are leading the way in raising the foundation for this future energy platform, and other states are just beginning that journey with smart meters, electric vehicles and DER. But there is no question that the electric utility industry, and the grid upon which it manages and distributes its product, is transforming. In this transformative period, utilities have a choice: they can view the challenge to their traditional ways of doing business as a threat, or they can turn it into a business opportunity to improve their investment performance, lower operating costs, and provide their customers with ways in which to participate that fit their changing expectations about the ways they use electricity. The transactive energy construct paves the way for this future vision, and IoT technologies will provide the tools for utilities to effectively manage this new, dynamic market exchange equation, balancing energy supply and demand and monitoring grid asset health in real-time. Taking the next steps End-to-end grid visibility, with the ability to manage, analyze and control additional grid- edge resources being added on an often-daily basis, will be imperative for utilities as the work their distribution grids is being asked to do evolves. The IoT enables utilities to create a scalable, flexible and more modular infrastructure that will be much better equipped to face new challenges, and to quickly adapt as markets and situations change. The Internet of Energy: Smart Sockets Source URL: http://www.azocleantech.com/article.aspx?ArticleID=641 Written by AZoCleantech Mar 25 2017 We waste too much energy and this is a direct cause of global warming. Imagine a fully integrated electrical system thatis safer, cleaner and sustainable. By utilising the Internet, Smart devices, sensors and switches technologists have designed systems that save energy in an intelligent fashion, saving the consumer money in the process. The Internet of things
  • 5. Sometimes the simplest ideas are the best: The Internet of Things uses the existing infrastructure of the Internet to allow devices to communicate and share data. These devices include sensors, Smart devices, lights, motors and vehicles as well as any compatible electronics. The advantages of such a system are increases in automation, accuracy, efficiency and experience quality; going beyond current “machine : machine” systems. It is estimated that the IOT will contain over 50 billion objects by 2020. The Internet of Energy As a subset of the IOT, the Internet of Energy (IOE) encompasses all objects involved in provision and use of electricity from the power grid down to individual electronic devices. The main objective of the IOE is to develop hardware, software and middleware for seamless, secure connectivity and interoperability achieved by connecting the Internet with the energy grids. The implementation of IoE services involves the use of multiple components, including embedded systems, power electronics or sensors; which are an essential part of the infrastructure dedicated to the generation and distribution energy. The Smart Grid Large territories have developed interconnected electrical supply systems that use the same voltages and currents; these are most evident in large countries/continents like USA, Brazil and the EU where the electrical grids are standardised. The IOE makes use of millions of sensors across the grid (devices, sockets etc) and integrated computing systems, connected using existing Internet infrastructure, allowing the prediction of future energy requirements: The Smart Grid. This affords huge savings in the amount of energy usage, in the form of fossil fuels and others. Encouragingly there are currently over 500 Smart Grid projects throughout the EU. Smart Energy Devices Smart socket devices on the market offer basic functionality that trails behind what has been achieved in the lab; available devices can turn off appliances, run schedules and monitor consumption but they are not fully automated ie. they do not respond intelligently to real time changes. The importance of Smart devices in the IOE cannot be underestimated and researchers at The University of Coruña have recently presented a system that monitors electrical usage in the home and optimises consumption according to user preferences and electricity prices. Researchers have a produced an integrated system that uses live electricity prices, obtained from the Internet, in order to optimise usage for the user. This system also self- organises, using the WiFi infrastructure so that it can collect data with minimal user intervention. All of the software is open source, allowing its modification by future developers and uses. The System Sensor and actuation subsystem: This controls the sensors and actuators of the system; responsible for collecting current data and for activating the power outlet when it receives a request from the control subsystem.
  • 6. Communications subsystem: This consists of wireless transceivers that join an auto- configurable star topology. Management subsystem: This provides the user with the possibility of obtaining the current status of all modules, modifying their configuration and acting directly on them remotely through a web interface. Control subsystem:This oversees controlling and managing the remaining subsystems, processing the data through the appropriate algorithms and acts as the gateway of the network to connect to the Internet. The Future of the IOE It has been demonstrated that this system can be used to operate devices at optimum times, saving energy and money (up to 70€ / year /device) by using online energy prices. It could also be optimised according to energy availability; for example, washing machines would be used at midday, when the electricity generated from solar panels is at a maximum. Smart sockets, thermostats and motion detectors are well established technologies that are integrated into the IOE in Smart Houses; these monitor all energy used by the home and data can be analysed / modelled for specific streets or areas. The Internet of Energy will ultimately provide a beautifully integrated system that monitors and predicts consumption patterns. Eventually systems like the one presented here will exist in all homes and feedback data that optimises power generation. This system will offer high levels of participation to the user; plug and play convenience for new devices; faster response to power outages and faults; and resilience to attack and natural disasters. The IOE can operate on a small scale, saving the user money in the home; as well on the grid scale, allowing more efficient electricity generation and decreasing fossil fuel usage. References 1. Steinbach, E., Kranz, M., Maier, W., Schweiger, F. & Alt, N. Advances in media technology. Camera5, 247–8 (2011). 2. Blanco-Novoa, Ó., Fernández-Caramés, T., Fraga-Lamas, P. & Castedo, L. An Electricity Price-Aware Open-Source Smart Socket for the Internet of Energy. Sensors17, 643 (2017) Google's big data calculates US rooftop solar potential Source URL: http://www.decentralized-energy.com/articles/2017/03/google-s-big-data- calculates-us-rooftop-solar-potential.html 20/03/2017 By Tildy Bayar Features Editor
  • 7. In an application of big-data capabilities to the decentralized energy sector, a project by Google has found that almost 80% of rooftops in the US are suitable for solar systems. Since its inception in 2015, the company’s Project Sunroof has analyzed around 60 million buildings in all 50 US states, determining overall that 79% have enough unshaded area to install photovoltaic (PV)panels. In sunnier states such as Hawaii, Arizona, Nevada and New Mexico, the analysis found that over 90% of rooftops could support PV, while rooftops in more northerly states such as Pennsylvania, Maine and Minnesota are only around 60% suitable. Among cities, Houston in Texas has the most solar potential, with an estimated 18,940 GWh of rooftop solar generation potential per year. Other sunny cities such as Los Angeles in California, Phoenix in Arizona and San Antonio in Texas follow in the rankings, with northern and often snow-bound (yet roof-plentiful) New York City in fifth place. [Native Advertisement] Google said the Project Sunroof tool uses imagery from its Google Maps and Google Earth in combination with 3D modelling and machine learning. For every building included in the data, Project Sunroof calculates the amount of sunlight received by each portion of its roof over the course of a year, taking into account weather patterns, the sun’s position in the sky at different times of the year, and shade from trees and tall buildings. This estimated sunlight is translated into energy production using industry standard models for solar installation performance. According to Google, if the top 10 cities reached their full rooftop solar potential, they could produce enough energy to power eight million homes across the US. Energy management: Oracle Utilities launches smart grid and IoT device management solution in the cloud Source URL: http://www.utilityproducts.com/articles/2017/03/energy-management- oracle-utilities-launches-smart-grid-and-iot-device-management-solution-in-the- cloud.html 03/23/2017 Energy management: Oracle has introduced Oracle Utilities Operational Device Cloud Service (ODCS), a new cloud offering that enables utilities to further automate the management of their grid assets and devices, at a total lower cost of ownership.
  • 8. The utilities industry is going through tremendous transformation as a result of IoT and increasing distributed energy resources. The United States alone has more than 70 million smart meters installed [footnote] and utilities are increasingly deploying smart field sensors. As each smart device has its own unique requirements for maintenance, inspection, firmware upgrades and security, utilities are struggling to manage the lifecycle of these assets in a single, centralized way. In response to these challenges, Oracle has unveiled a cloud-based version of its Operational Device Management Solution that provides a scalable and future-proof way to manage IoT device operations. Available as a new stand-alone cloud service, ODSC automates the management of smart grid and IoT devices. When combined with Oracle Utilities Work and Asset Management solution, it delivers a unified solution in the cloud to extend asset performance management to smart devices at a massive scale. This complete visibility of smart assets delivers detailed insights into each device’s location, characteristics, health, and firmware upgrade status. In addition, utilities can extend ODCS for customer—owned asset registration processes such as smart thermostats and solar PVs. Additionally, by leveraging the cloud, utilities can reduce their total cost of ownership. “We’re in front of the dramatic shifts the utilities industry is experiencing, providing new technologies that meet the needs of our customers as they navigate this changing landscape,” said Rodger Smith, general manager and senior vice president for Oracle Utilities. “We’re committed to innovation, and to providing cloud solutions that make operational excellence a reality for electric, gas and water utilities worldwide.” The solution can be added to Oracle Utilities Work and Asset Cloud Service and Oracle Utilities Meter Data Analytics Cloud Service or used as a stand-alone solution depending on a utility’s requirements. New Features in Oracle Utilities Operational Device Management Cloud Service: • Proactively adjust, update, and repair smart grid and IoT devices as needed • Enable significant cost savings by eliminating labor costs due to physical data collection with automated processes • Reduce total cost of ownership by using the most up to date IT infrastructure in the cloud and alleviating the need to continually maintain older systems • Find risks of device failures faster with increased visibility into the age and reliability of each device • Prepare for asset registration capabilities of customer-owned assets Are vehicles the mobile sensor beds of the future? Source URL: http://readwrite.com/2017/03/22/are-vehicles-the-mobile-sensor-beds-of- the-future-tl1/ Posted on March 22, 2017 in Connected Devices, Smart Cities, Transport
  • 9. When people think of a car, they think of the thing that gets them from one place to the next. Traditionally they have been just that: a tool with a single function – to get someone, or something, from one place to another. With the advent of new vehicle designs and the addition of new technology, that is going to change. Just like phones have evolved over the last two decades from a single purpose tool to one with countless functions, vehicles are now undergoing something similar. New vehicles are being built with an increasing number of sensors. These sensors are not only measuring how the vehicle is operating, but are starting to measure the environmental conditions they are being used in too. Future vehicles will effectively become mobile sensor beds, collecting data, at a granular level, across the whole planet. The massive amounts of data being generated will be perfect for the application of machine learning. The created algorithms will have an unprecedented level of understanding on how the environments outside the vehicles will change over time, Imagine a car that selected a playlist based on driving conditions. Or that knew an icy patch was up ahead because the car that drove past that point an hour ago sensed wet road conditions and the temperature has just dropped to the point that it will freeze. These are just the tip of the iceberg on some of the things machine learning will bring to vehicles on the road. Startups are leading the charge Current technology tends to revolve around the creation or aggregation of data with an intended future application to machine learning. Nauto and UrbanLogiq are two startups in this space. Nauto is building a data set to help OEMs and other partners develop the next generation of autonomous capability for vehicles in urban areas. However, their data set also includes things such as road conditions and how they change over time. This could be used, alongside machine learning, in the future to determine when and where cities should do maintenance to optimize their budgets and road safety. UrbanLogiq is not building a data set, but preparing governments for the arrival smart car technology. They’re building a platform that would integrate data from systems like Nauto with the government’s own traffic sensor data to facilitate responsive traffic light timing. Using machine-learning, this aggregation of data will help city planners understand and predict the evolution of their communities This month, Google has also made a play in this space to tackle a common pain in city driving – finding where to park. They are using the data they collect to create predictions on where there might be free parking. Creating an intelligent future These technologies are just the start of how environment data collected from vehicles will change the world. With millions of vehicles on the roads every day, they will be collecting
  • 10. data everywhere and on potentially everything they come across. A change that will probably happen in the near future is related to weather data, patterns, and forecasts. Each vehicle could be constantly collecting temperature, pressure, and potentially even wind speed and uploading all that data to a centralized system. With millions of vehicles on the road, you have a geographic data set that is extremely granular allowing strong predictions on how the weather will change over time. With machine vision added to these vehicles, the possibilities increase exponentially, allowing for exact positioning of lightning, and high-resolution, three-dimensional modeling of storm fronts. Once you have strong weather predictions you can merge the data set with supply chain data. This will allow companies to optimize their supply chain and inventory based on future weather. The concept of shelves being out of stock due to weather or a manufacturing bottleneck due to parts being unexpectedly delayed will become a thing of the past. Companies will be able to leverage theenvironmentaldata coming off vehicles to allow them to optimize their operations around future weather. Another situation you will see is machine learning driven advice on when to schedule events. You might be able to get a warning that by scheduling an event at one time, the weather coupled with traffic will make it take an hour to get there. However, if you schedule it an hour earlier, it may only take 15 minutes. Environmental sensors could even be merged with sensors monitoring the driver or passengers in the vehicle. Knowledge of what conditions make a driver feel stressed or relaxed could be used to determine when they should drive or be driven for them to feel best. We can look forward to a future where our vehicles will understand the environments they will be operating in and how that knowledge will be used to optimize our lives. Allowing vehicles to understand the environment Rethinking what a vehicle is. Vehicles transitioning from simply a transportation tool to a series of sensors that travel across the world. These sensors could pick up changing road conditions or weather patterns. These large new data sets can then be used by governments (road repairs), insurance, or routing purposes and will allow people to make the best data-driven decisions.
  • 11. This article is part of our connected cars series. You can download a high-resolution version of the landscape featuring 250 companies here.