Between the Poles

Hand held scanners closer to revolutionizing the construction industry

At the SPAR International Conference in April 2014, Kirk Knorr from Burns & McDonnell and Gregory Lawes of point3D gave a presentation about their experience using a handheld scanner from DotProduct LLC , a relatively new startup.  This is a professional device intended for engineers and others working in the construction industry.  It is basically a 7" Android tablet with a compact near infrared structured light and rgb 3D imaging system.  It weighs less than a kilogram and is accurate for engineering purposes at distances up to 3.3 meters.  It costs thousands of dollars, much less than the tens of thousands of dollars for terrestrial laser scanners.  Kirk Knorr and an engineer from Bechtel reported that he had been using the device on live construction projects for a year and in their view the DotProduct and similar handheld devices are going to revolutionize how we do construction. They foresaw this happening very soon, within a year.

Now a major metrology company FARO has announced the Freestyle3D Scanner, which is a high precision, handheld scanner which generates high-definition point clouds.  It can be used to scan objects within a range of half a meter to 3 meters away with a resolution in 3D of  better than 1.5mm with a image point density of up to 45,000 points/m² at 0.5m and up to 10,500 points/m² at 1m.  The total scan volume can include up to 8.1m³.  The device weighs less than a kilogram with dimensions 26cm x 31cm x 10.5cm.  The scanner is attached to a Microsoft Surface Pro tablet for visualizing the point cloud as you scan.

Some of the applications of the scanner include architecture and interior design, restoration and 3D modelling, construction and facility management, and forensic applications including accident reconstruction.

Thanks to LiDAR News for pointing me to this.

Smart power spatial power

For the first time in a hundred years, the electric power utility industry is undergoing a momentous change. Distributed renewable power generation, especially solar photovoltaics (PV), is introducing competition into an industry that has been managed as regulated monopolies. Consumers with solar PV panels on their roofs (and in not-too-distant future with Tesla batteries in the basement) and companies like Solar City (co-founded by Tesla co-founder Elon Musk) are fundamentally changing the traditional utility business model. A recent report from the Edison Electric Institute (EEI) report refers to disruptive challenges that threaten to force electric power utilities to change or adapt the business model that has been in place since the first half of the 20th century.

As a result, every aspect of the the electric power industry is changing. One of these changes involves the role that geospatial data and technology play in the electricity industry. In the past, geospatial has been a tactical tool — it was (and still is) used in a variety of applications — in outage management, asset management, mobile work- force management, energy density modelling, vegetation management, demand modelling, transmission line siting, substation siting and design, energy performance modelling of buildings, disaster management, and mapping renewable resources, to name just a few. However, with the changes that the industry is undergoing now, geospatial is poised to become a foundation technology for the smart grid.

The Energy Issue of Geospatial World Magazine explores the impact that this momentous change is having on the application of geospatial technology in the electric power utility sector.  Below I'm providing an overview of the material relating to electric power you'll find in this issue.

GIS has been widely used by utilities for years for automated mapping/facilities management, back office records management, asset management, transmission line siting, and more recently for design and construction, energy conservation, vegetation management, mobile workforce management (MWFM), and outage management (OMS). Now, utilities are integrating GIS with automated meter infrastructure (AMI) and supervisory control and data acquisition (SCADA) systems. Intelligent design has crossed over from the office to the field in utilities, also enabled by the capabilities of GIS, says Smith. Geospatial-related analytics (spatial analytics) is seen as one of the key aspects of success for electric utility operations in the smart grid era. Looking for patterns and correlations between different land, weather, terrain, assets, and other types of geodata will be increasingly important for utilities. Power-related analytics with geospatial components include network fault tracing, load flow analysis, Volt/VAR analysis, real-time disaster situational awareness, condition-based maintenance, and vegetation management. The smart grid is all about situation awareness and effective anticipation of and response to events that might disrupt the performance of the power grid. Since spatial data underlies everything an electric utility does, GIS is the only foundational view that can potentially link every operational activity of an electric utility, including design and construction, asset management, workforce management, and outage management as well as supervisory control and data acquisition (SCADA), distribution management systems (DMSs), renewables, and strategy planning.

Peter Batty reports on the major growth in geospatially-enabled Web and mobile applications with a special focus on the open source geospatial community and the significant impact of these technologies in the utility sector. "In general, there are a lot of geospatial open source software components available now that have the capabilities and robustness to be used in serious enterprise applications."  John McDonald, Chairman of the Smart Grid Interoperability Panel has been a firm believer for a long time that geospatial information is part of the foundational platform for smart grid.  SGIP has signed a memorandum of understanding with the Open Geospatial Consortium with the goal of incorporating more geospatial standards into SGIP standards.  Cindi Smith of Bentley goes even further and argues that  “geospatial technology is already a foundational component of electric power utilities’ IT/OT systems.  Smart grid simply brings more focus to the role it can play by virtue of the visibility of smart grid projects and processes in a utility and their need to exploit the vast amounts of data produced by the smart grid." Loek Bakker & Jan van GelderIt of Alliander, a Dutch utility company, describe how essential it has been for Alliander to integrate GIS, ERP and SCADA systems for a correct picture of its assets.  As electric utilities evolve into increasingly data-driven organisations, Jeffrey Pires and G. Ben Binger describe how GIS is fast emerging as the backbone for data management platforms. 

Cities are beginning to develop 3D models of underground infrastructure motivated by new underground remote-sensing technologies and by ROIs of up to of US$21.00 saved for every US$1.00 spent on improving the quality level of subsurface utility information.  Steve Dibenedetto, Senior Geoscientist and Technology Manager, Underground Imaging Technologies (UIT), part of Caterpillar describes new remote-sensing technology for detecting and geolocating in 3D underground utility infrastructure such as Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI). 

The Indian on-going Restructured – Accelerated Power Development and Reforms Program (R-APDRP) is one of the largest IT initiatives by electric utilities anywhere in the world — in one integrated project, all state-owned distribution utilities in India are building IT infrastructure, IT applications and automation systems.  The programme set out to create baseline data in the form of consumer indexing, GIS mapping and asset mapping. Reji Pillai & C. Amritha assess how GIS can be applied in this context.  

Integrating  geospatial and BIM is a key enabler for energy performance modeling which is a fundamental instrument for reducing the energy consumption and improving the energy performance of new and existing buildings. According to a report from Navigant Research, global zero energy buildings revenue is expected to grow from $629.3 million in 2014 to $1.4 trillion by 2035.

Wolfgang Eyrich of Entegra shares how Entegra’s primtech product, which is designed to help substation designers deliver designs based on integrated product modelling, provides a geographical context to substation designing. 

Matt Zimmerman of Schneider Electric highlights one of Schneider Electric's key techologies "graphic work design" which is integrated geospatial and engineering design (CAD or BIM).  Schneider Electric's geospatial division focuses on developing integrated, location-aware enterprise solutions such as integrated outage management (OMS), customer information system (CIS), GIS, and external weather reporting and forecasting service to help plan crew deployment during a storm.  Matt foresees that location-aware predictive analytics for electric networks is going to be one of the major development areas for utilities in the future.  Brad Williams of Oracle points out that spatial analytics is becoming a key technology for electric utilities because everything a utility does - customers, assets, and operations - involves location. 

One of the biggest challenges that utilities are experiencing is increasing volumes of structured and unstructured data (big data) that is overwhelming traditional enterprise systems.  The structured data comes from smart meters and intelligent electronic devices, and the unstructured data from social networks including Twitter, Google, Facebook and other social applications.  Consumerization of geospatial technology (we are all GPS-enabled sensors) will enable crowd-sourcing new sources of information about electric power networks most of which involves location (big spatial data).

Oracle Database Cloud Service supports Spatial

At Oracle Open World in San Francisco 2014, September 28–October 2 the Oracle Spatial and Graph SIG held a Meetup.  By way of background Oracle Spatial and Graph support geospatial data and analytics for land management and GIS, mobile location services, sales territory management, transportation, LiDAR analysis and location-enabled Business Intelligence. The graph features include RDF graphs for applications ranging from semantic data integration to social network analysis to linked open data and network graphs used in transportation, utilities, energy and telcos and drive-time analysis for sales and marketing applications.  

There were several very interesting discussions at the Meetup that revealed some interesting aspects of Oracle Spatial itselef and its interoperability with other products such as ESRI ArcGIS, Autodesk Map3D, and Bentley.  These are taken from a summary recorded by Nick Salem moderator of the Meetup.

The Meetup was attended by about 20 users came from industries such as rail, local city government, national land management agencies, and defense. The SIG Board and members of the Oracle Spatial product development team joined up with them in the Oracle Technology Network Lounge.

Some of the most interesting discussion topics include new features in Oracle Spatial 12c and real world experience interoperating Oracle Spatial with CAD and GIS products from other vendors.

• Oracle’s new Database Cloud Service offering now includes Spatial. 
• A new Oracle Spatial 12c SDO_POINTINPOLYGON function can be used to ingest large point datasets (point clouds) without the overhead of creating a spatial index.
• Bechtel has developed a way to use ESRI ArcGIS versioning with Oracle Workspace Manager (OWM).  They have developed in-house custom tools to usefeature-level metadata to be able to retrieve spatial content from their project and public spatial databases, as well as to compile the revision history of layers in the database to retrieve maps impacted by changes to individual features.
• Dan Geringer, Oracle Spatial Solutions Architect, advised that other large enterprises have also successfully implemented OWM with ESRI ArcGIS.
• Bulk processing and interoperability are two of the important advantages of Oracle Spatial for enterprises. Bechtel has large project-based deployments of Autodesk and Bentley CAD systems, and has worked with Autodesk in recent years to successfully write spatial data to their Enterprise GIS Oracle Spatial database from Autodesk Map 3D. They also have developed a GIS Desktop Procedure that details the required Autodesk client software configuration for Oracle Spatial and ESRI ArcSDE database connections. They will be updating it for use with Autodesk 2014 and 2015 clients.
• Latest version of MapViewer (11.1.1.7) supports HTML5 and JSon and the ability to work in disconnected mode. Standalone, web-based vector editing is also available. Wish Li and Jayant Sharma demonstrated  MapViewer on mobile devices, an Android phone and an iPad.

 

Mobile scanning interiors of buildings with automatic feature extraction for energy performance modeling

At the SPAR International conference Avideh Zakhor from the University of California Berkeley gave an enthralling presentation about her research on capturing optical and thermal point clouds of the insides of buildings using a portable backpack containing a collection of sensors.   Her team has also developed analytical software tools for generating floor plans, distinguishing rooms, identifying staircases, texture mapping surfaces, identifying windows, finding heat sources such as computers and human occupants, identifying lights, and even estimating plug load lower consumption - all automatically. The software her team has developed can generate input in the form of an IDF file for the Department of Energy's EnergyPlus energy performance analysis program. Avideh said that soon it will also be able to generate a gbXML file, which can be consumed by almost all building energy performance analysis software.

Man portable system

 

The "man portable system" her team has developed is a 32 pound backback with a collection of sensors.  There are sensors for accurately tracking the six degrees of spatial freedom which determine the location and orientation of the backpack in addition to sensors for recording optical and thermal point clouds. The operator walks through the building going into all rooms, halls, stairwells and other human accessible spaces. With the backback this is a much faster process than capturing indoor spaces with static laser scanners. For example, Avideh's team was able to scan Union Station in Washington DC in a matter of hours. A comparable static scan takes days.

 

Automated feature extraction

 

The resulting georeferenced data is then offloaded from the backpack and analyzed to generate different 3D data products including optical and thermal 3D point clouds, a colourized 3D point cloud, surface texture map,  and triangulated mesh surfaces.  Two different triangulated surfaces are generated for different applications - a very detailed surface and a much simpler model of spaces and walls. Using these data products the software automates feature extraction. It can distinguish  windows, staircases, and individual rooms and generate a floorplan.  Surface textures can be added to create a 3D photorealtistic rendering.  By analyzing both the optical and thermal point clouds the software tools can identify heat sources including computers and human occupants and can even identify lights and estimate power plug loads.

 

Building energy performance modeling

 

Usi‎ng the results of the automated feature extraction the software tools can be used to generate the input required for a building energy performance audit. Currently the tools are able to generate input in the form of an IDF file for the Department of Energy's Energyplus whole building energy simulation program.   Avideh said that soon it will be possible to generate an gbXML file, which can be consumed by most building energy performance analysis applications including IESVE and Green Building Studio.  This clearly has the potential to convert what is now a slow, manual, expensive process into a fast, repeatable, affordable process.

Handheld scanners set to revolutionize construction

At the SPAR International Conference today Kirk Knorr from Burns & McDonnell and Gregory Lawes of point3D gave a presentation about their experience using a handheld scanner from DotProduct LLC.  This is a professional device intended for engineers and others working in the construction industry.  It is basically a 7" Android tablet with a compact near infrared structured light and rgb 3D imaging system.  It weighs less than a kilogram and is accurate for engineering purposes at distances up to 3.3 meters.  It costs thousands of dollars, much less than the tens of thousands of dollars for terrestrial laser scanners.

To use it, you walk through or around the area of interest holding the scanner in your hand.  It is particularly good at getting into spaces that a traditional tripod-mounted laser scanner can't see.  Another major advantage is that the processing is done in near real-time on the Android tablet so that when you have finished scanning you have a point cloud on the tablet that you can visualize in 3D and verify that you've got everything you need before you leave the site.  You can then download the point cloud from the DotProduct device to a laptop or other device running the same industry standard software for manipulating, analyzing measuring or visualizing the point cloud that you've always been using.

Kirk Knorr described how he successfully used the DotProduct device on a live engineering project.  Another engineer from Bechtel reported that he had been using the device on live construction projects for a year and in his view the DotProduct and similar handheld devices are going to revolutionize how we do construction.  He added that he foresees this happening very soon, within a year.  Another engineer in the aerospace industry said that his company intended to get one of these devices into the hands of all of their technical staff.

Major benefits realized from ensuring quality geolocation data for utility assets

At the National Rural Electric Coop Assn (NRECA) TechAdvantage Conference in Nashville, Nathan Frisby, GIS Engineer at Big Sandy Rural Electric Coop (RECC), and David Herron of Leidos gave a presentation about their experience implementing a GIS at Big Sandy.that I think would be of interest to any utility that has data quality issues, in other words, most utilities.  Their experience  was particularly notable because Big Sandy is a very small utility with about 13,200 customers and commensurately limited IT resources, but they managed to get the data quality part right. I've blogged on many occasions about the challenge of data quality of location information at utilities. It is a major challenge, and one that the move to smart grid is forcing all utilities to address. Big Sandy  focused not only on ensuring that the location and other data they captured was accurate and up to date, but they implemented business practices to ensure that the high level of data quality is maintained.   

Big Sandy RECC provides electric power services for 13,200 members in an 8 county territory in Kentucky that is too rural to be of interest to the investor owned utilities.  The people in the area got together and formed a coop in 1940.

Collecting location data

The first step in the process they went through was a GPS inventory of everything in the field including meters, poles, transformers, lights, fuses, and so on.  As part of this effort they physically tagged all their poles with a unique serial number.  When they inventoried poles they captured everything on them including transformers, conductors, insulators, cross arms and equipment from other utilities such as the local phone company (joint use).  But they went one step further and noted any problems such as broken cross arms, cracked insulators, or rotten poles. This amounted to a full inventory plus a full field inspection.  One of the reasons this was so successful is that the folks that conducted the inventory were a dedicated team whose sole responsibility was the GPS inventory.  

Another thing they did at the same time that was also critical to down the road was linking customers addresses to meters and meters to transformers.  As I have blogged about, linking customers' addresses to meters is a challenge for many utilities, but it is essential for  many critical applications including outage management.

Maintaining data quality

Their data quality maintenance program is basically a double check system.  The field worker, typically a linesman, records the changes he/she makes on the work order which is returned to the records team.  In addition once a month, a supervisor takes all the completed work orders and goes out in the field and verifies the changes recorded on the work order, looking carefully for any deviations between what he finds in the field and what is recorded on the work order.  Only after that is the asset database updated.

Benefits

Some of the significant benefits that Big Sandy has realized by implementing a GIS with ensured location data quality include,

• Greater resilience - outages are fewer and of shorter duration because reliable location data fro their assets means they can respond faster.  Linesmen non only know exactly where a downed pole is, but also exactly what equipment is on the pole.  Nathan Frisby said he was uncertain whether he would be able to attend the NRECA conference to give his talk because they experienced an ice storm in the beginning of the week.  But he said that their distribution system is so much more reliable now that he was able to make it to the conference.
• Reliable reporting to RUS and FEMA - They found idle transformers, power lines that were not on any paper maps, and duplicate transformer numbers.  For 1500 transformers the data currently in the database was incorrect and had to be corrected.
• Improved disaster response - When they have a storm and get assistance from nearby power utilities, they are able to provide reliable maps to direct the folks from other utilities who are not familiar with the service territory to poles and other assets that need servicing.
• Fewer truck rolls to respond to 811 One Call Center - They were able to reduce the number of truck rolls because they know precisely where all their assets was and often did not have to roll a truck.

Perhaps the most telling benefit is how it has improved their ability to report after a disaster to FEMA.  For example, after an ice storm in 2012 that fortuitously had hit an area they had GPS inventoried some time prior to the storm, it helped them report accurately their claims for damages to FEMA.  When the FEMA inspector visited them to verify their claims, she randomly selected 12 poles and then asked to go out in the field to visit those 12 poles to verify that what was recorded on the work orders corresponded to the work that had actually been done on the assets.  After visiting three poles and comparing the very detailed information that Big Sandy had recorded, she was so impressed with the accuracy and detail, she said that this was the most detailed and reliable data she had seen and she didn't need to visit any more poles.  Very impressive!

I would also add that the high quality of their spatial data means they are well prepared for smart grid.

Report predicts that low cost LiDAR will be disruptive in next 5 years

Markets and Markets has released a report that analyzes the LiDAR (Light Detection and Ranging) market by product types (airborne, mobile, terrestrial and short range) and applications (government, civil engineering, military/defence/aerospace, corridor mapping, topographic surveying, and volumetric mapping)  and provides global forecasts for the period  2013 – 2018.  

LiDAR has been traditionally applied to produce 3D digital elevation and terrain models typically for forestry and civil engineering applications.  But corridor mapping (for example, for transmission lines), which uses mobile LiDAR systems as well as airborne LiDAR, is projected to be the application with the highest annual growth rate from 2013 to 2018.

The report estimates that the global LiDAR market was worth $218.9 million in 2012.   Civil engineering was the most important application.  Most of the revenue was derived from airborne lidar systems, partly because they are relatively expensive.  But this is changing. The report forecasts that the global LiDAR market will grow by more than 15 % annually over the next five years, reaching $551.3 million in 2018.  The report predicts that airborne LiDAR systems will have the lowest compound annual growth rate among the four types of LiDAR systems and projects that the revenue associated with terrestrial and mobile LiDAR systems will surpass that of airborne LiDAR systems by 2018. 

The report also forecasts that low-cost LiDAR systems could revolutionize the surveying industry in the next five years.  I blogged recently about a light weight UAV-mounted LiDAR platform weighing less than 10kg which combines UAV, LiDAR and GNSS technology and is designed as a micro-mapping solution.

Geopatial data and technology projected to be a foundation for interoperable smart grid operations

At the Second Annual Summit on Data Analytics for Utilities in Toronto, Brad Williams, Vice President of Utilities Industry Strategy at Oracle, made the case that in the context of smart grid spatial analyics is going to be a key technology because everything a utility does (customers, assets, and operations) involves location.

Brad outlined a number of areas where spatial analytics are going to be applied including reducing non-technical losses, targeting demand response, distribution operations planning, transformer load management, data quality, voltage correlation (linking meters to transformers), energy modeling, voltage deviation monitoring, geographicl outage frequency analysis, and predictive analytics for electric vehicle adoption to name just a few.

Brad's analysis is supported by a 2012 report from Navigant (Pike Research) that forecasts that the increasing penetration of GIS into smart grid workflow applications, such as MWFM, DMS, energy management systems (EMS), OMS, customer information systems (CIS), and analytics will be the primary driver for electric utility GIS software and services growth with an annual growth rate (CAGR) of 12.8%, increasing from $1.8 billion in 2011 to $3.7 billion in 2017. Navigant expects that in there will also be growth, but at a slower rate, in GIS in utility construction and engineering-related GIS applications driven and this will be led by the power grid build-out in Asia Pacific.

Smart grid will make GIS a foundation technology

GIS is currently applied tactically by utilities in several areas.  GIS has widely used by utilities for years for automated mapping/facilities management, back office, and plant and infrastructure architecture, engineering, construction (AEC).   Increaslngly it is also being used for asset management, mobile workforce management (MWFM), and outage management.  But smart grid is going to make GIS strategic.  GIS is already being applied to AMI, DMS and integrated with SCADA by early adopters.    Navigant project that with the development of the smart grid, GIS will become a foundation technology for interoperable grid operations. 

"The smart grid is all about situation awareness and effective anticipation of and response to events that might disrupt the performance of the power grid. Since spatial data underlies everything an electric utility does, GIS is the only foundational view that can potentially link every operational activity of an electric utility including design and construction, asset management, workforce management, and outage management as well as supervisory control and data acquisition (SCADA), distribution management systems (DMSs), renewables, and strategy planning.

Navigant sees the the challenges to effective adoption and use of GIS in the electric utility involve data complexity and quality, mobile workforce requirements, loss of GIS knowledge and skills through retirement, organizational structure, and the GIS vendor ecosystem.

An analysis by Research and Markets entitled Global GIS market in the Utility industry 2012 - 2016 projects that the utility GIS market will grow at a CAGR of 10.37 percent over the period 2012–2016. Research and Markets sees one of the key factors driving this market growth is the growing need for knowledge infrastructure. But it specifically targets the lack of awareness about utility GIS in developing countries as a potential inhibitor to market growth

Other challenges relevant to the utility GIS market include data quality, managing the mobile workforce, and changing the organizational structure of utilities. .

Data quality
Navigant identifies a history of poor GIS data quality as a major problem in the utility industry and reports that poor GIS data quality is an area of significant concern for smart grid planners who plan to use GIS as a foundational data layer for interoperable grid operational processes.  I have blogged about the challenge of data quality in the utility industry on a number of occasions. 

At a recent conference a speaker from a Canadian power utility emphasized that a key prerequisite for a successful data-driven analytical approach for utilities is quality data.   His utility found that when they started to make investment decisions based on their analysis of their operational data, the deficiencies in their data sets immediately become apparent.  For example, they found that only 76 % of their connectivity data was reliable, the remaining quarter was unusable.  To ensure the necessary level of data quality and reliability data governance (processes that ensure that important data assets are formally managed)  was a key underpinning of his utility's strategy.    They implemented major projects to cleanup their connectivity and other data.  Realizing that data quality is perishable, they also implemented a data governance policy and focused on improving business processes that produced bad data.  For example,  the processes for managing as-builts is major challenge for many utilities as I have blogged about on multiple occasions, most recently here.

Mobile workforce requirements
Navigant estimates that 60% of all electric utility employees work in the field on assets that have spatial attributes. It also points out that managing a field workforce is a significant challenge, when data including location about assets in the field are missing or incorrect.

Organizational challenges
Navigant sees the divide between the information technology (IT) and operations technology (OT) sides of the business as an inhibitor to smart grid adoption. Navigant sees GIS as a critical technology to bringing these two sides of the business together.

Transforming the utiility GIS market
A critical factor is depth and quality of the skills, tools, and solutions that are available to support GIS-based applications . The traditional vendors in this space are Esri, Intergraph, Autodesk, Bentley, GE/Smallworld, and Oracle, but Navigant sees that the integration of IT and OT to support smart grid is going to transform the market through mergers and acquisitions.  The effect will be to dramatically increase the size of the market.

GIS has had limited implementation in smart grid applications such as SCADA, EMS, DMS, and advanced DMS(ADMS) and is in the innovator stage of adoption in this area.  Some of the technology developments in GIS-related applications that Navigant sees as becoming important include geospatial database developments relevant to utilities such as "real-time big data", cloud, mobility and communications technology, 3D, and remote sensing.

Spatial analytics

Navigant sees geospatial-related analytics (spatial analytics) as the key to the success of electric utility operations in the smart grid era. Geospatial data overlays to search for patterns and correlations between different land, weather, terrain, assets, and other types of geodata will be increasingly important for utilties. Power-related analytics with geospatial components include network tracing, load flow analysis, and real-time network analysis. Real-time and historical outage situational awareness, device failure and maintenance history, reliability, and vegetation management also require spatial analytics.

Geospatial data is also critical for analytics relating to long-term power system evolution. Analyzing structured and unstructured data sources to uncover patterns in the data isa  growing area but will require high performance computing to enable it to be applied in near real-time.

Navigant points out that one of the challenges is that many utilities have numerous siloed GISs and concludes that "GIS usage in smart grid applications will demand a high degree of accuracy and timely, synchronized updates, which will be difficult to orchestrate in a federated environment. Ultimately, utilities will have to implement a GIS repository of record that supports smart grid requirements."  To me this means that the stage is set for a transformation in how utilties use GIS that will make it a foundation for managing the smart grid and fully realizing the benefits of smart grid technology.

OGC's Geopackage standard enables geospatial data sharing for mobile devices

The Open Geospatial Consortium's draft GeoPackage (GPKG) standard is an open, app-independent, platform-independent, portable, interoperable, self-describing data container and API.  This standard is intended to support multiple mapping and geospatial applications such as fixed product distribution, local data collection, and geospatially enabled analytics.

The standard was developed for mobile device users who require geospatial apps, but operate in environments with limited network connectivity, in other words, connection to a network may be intermittent.  At present each mapping or geospatial app requires its own geospatial data store.  This creates noninteroperable data silos.  App-specific data silos contain the same geospatial data but are not accessible by more than one application.  The Geopackage standard is intended to define a common data store that is accesssible to all apps through a common API.  This means that several apps can share the same data. The standard is intended to not only be app independent, but also platform independent so that it can be be used by apps on iOS, Android, Blackberry, and other devices.

GeoPackages provide direct access to vector geospatial features and tile matrix sets of earth images and raster maps at various scales. Direct use means the ability of apps to access and update data through an API in a “native” format without intermediate format translations.

A GeoPackage is a platform-independent SQLite database file that contains GeoPackage data and metadata tables. What is allowed in a GeoPackage is entirely defined by the encoding standard specification.

An Extended GeoPackage is a GeoPackage that contains additional data elements (tables or columns) or SQL constructs (data types, functions, indexes, constraints or triggers) that are not specified in the encoding standard.

The Geopackage standard is the first OGC standard to use Github to host the standards development documents.

McKinsey identifies renewable energy and energy storage as disruptive technologies

McKinsey Global Institute (MGI) has identified 12 technologies that could cause large-scale economic disruptions in the future.  MGI estimates that the 12 technologies combined could have a potential economic impact between $14 trillion and $33 trillion a year in 2025.

1 Mobile Internet $3.7 - 10.8 trillion
Wieless, small devices, advanced displays and batteries

2 Automation of knowledge work $5.2-6.7 trillion
Artificial intelligence, big data, natural user interfaces

3 Internet of things $2.7-6.2 trillion
low-cost sensors, wireless and near-field comms devices like RFID

4 Cloud $1.7-6.2 trillion
Virtualization, metering, data-center h/w, high-speed networks, SaaS

5 Advanced robotics $1.7-4.5 trillion
Computer vision, sensors, advanced robotic dexterity, sensors

6 Autonomous/near-autonomous vehicles $0.2-1.0 trillion
Artifical intelligence, computer vision, advanced sensors (radar, LiDAR, GPS), m2m comms

7 Next-generation genomics $0.7-1.6 trillion
Advanced DNA sequencing, DNA-synthesis, big data and analytics

8 Energy storage $0.1-0.6 trillion
Battery technologies, pumped hydro/compressed air, advanced materials/nanomaterials

9 3-D printing $0.2-0.6 trillion
Selective laser sintering, fused deposition modeling, stereolithography, direct metal laser sintering

10 Advanced materials $0.2-0.5 trillion
Graphene, carbon nanontubes, nanoparticles, smart materials (piezoelectric materials, memory metals, self-healing materials)

11 Advanced oil and gas exploration and recovery $0.1-0.5 trillion
horizontal drilling, fracking, microseismic monitoring

12 Renewable energy $0.2-0.3 trillion
SolarPV, wind turbines, concentrated solar, hydroelectric and ocean-wave power, geothermal