How does the gap between sensors, systems and analysis get filled?

by Matt Ball on March 25, 2011

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The idea of networked sensors informing systems for intelligent infrastructure to improve efficiency has been a topic of coverage here for a while, and it’s reaching a whole new mainstream momentum. Of course, much of this is due to the push of one high-profile vendor, with a sustained advertising campaign that promotes smarter water, smarter transportation, smarter cities, and a smarter planet. But, who doesn’t want to be smarter?

There are plenty of opportunities for a broad application of sensors and systems to improve efficiency, and many of these are in the traditional geospatial markets. Will geospatial technology form an important integration role between systems and sensors, and provide a means to gain insight from all the data? There is certainly that potential.

Sensor Systems

All the traditional GIS markets would benefit from more real-time or near-real-time inputs about status and condition of their networks or geographies. Sensors add the ability to return impartial and constant  measurements for a myriad of parameters, particularly for changing conditions.

The benefit of smart sensors, the next-generation of sensors that move from analog to digital, is that they can automatically communicate with each other, and can self-configure and calibrate due to a common communication and interface. They are also easier to deploy because wireless capabilities drive down installation costs.

In large networked companies such as the utilities, there has been a long history of sensors to return customer details, such as automated meter reading, and this is rapidly evolving to encompass returning all manner of details regarding the status of the grid. In turn, developments in the smart grid are spreading to other networks such as water.

The benefits of smart sensor grids will be realized on individual networks, but also at the level of networks that can communicate and respond to one another. Imagine the benefits of a network in times of great demand and stress or when a disaster impacts the grid. A smart network can respond to an incident by shutting itself down without the threat of collateral damage to others on the network or of widespread disruptive damage such as a water main break. The savings in reduced damages alone would justify the cost, and the coupled efficiency savings means that investments can quickly pay off.

Standards at the Forefront

Just this week, IBM purchased a company that integrates sensors and software for optimizing building efficiency. This purchase was accompanied by a press release that outlined some tired reasoning about the benefits to consumers in regard to integration. The argument is that before this purchase, and integration with other elements in IBM’s fold, customers would have to deal with many siloed systems that are difficult to integrate.

Luckily, there has been a strong groundwork of sensor standards that are well out in front on easy integration, and that serve to create a level playing ground among vendors and systems, wiping away the argument that standardization within one company’s architecture is the way to avoid integration issues. An open architecture built on web services allows for communication between sensors, provides a framework for encoding and archiving observations, and provides a means for sensors to discover each other and communicate readings. These standards are coupled by smart sensor standards on the hardware side so that hardware can be communicated with through a standard set of interfaces.

Big Data and Analysis

There’s a growing acceptance that a data-driven understanding of the world is the way to make sense of all the changes that we’re experiencing. The pace and implications of global change are only seeming to accelerate, and our ability to collect more data faster is the only way to get a handle on this rapid change. The more data that you gather, as it turns out, the faster you’re able to make sense of whether new data is good news or bad.

While efforts are made on how to store, access, and integrate these massive amounts of data, the natural role of geography as an integrative discipline can’t be overlooked. Making sense of data through the common denominator of place yields great insight, particularly when coupled with time. This spati0-temporal signature is one of the key elements to understanding the uniqueness of observation, and the aggregate of observation around place gives context to understand change and relationships that wouldn’t be accessible in other ways.

As we add sensors to our networks and systems, and as these inputs proliferate, our understanding of our world will increase. Geospatial technology, in its role of describing and making sense of the world, is a natural glue between sensors and systems to provide the insights that are needed to make better decisions for our planet.



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