Creating smarter, more connected energy ecosystems with Big Data

The amount of data being generated by connected devices and sensors embedded in machines and systems of all kinds is reaching unprecedented levels. In fact, IDC forecasts that sensor-generated data will increase to 42% of all data by 2020, up from 11% in 2005.

The good news is this phenomenal growth is enabling new sources of organizational and customer value. By collecting and analyzing vast amounts of sensor data, many industries, from product manufacturers to large-scale farmers, are redefining operational planning, product development, customer service, and business processes.

3 ways to put energy IoT data to work: Buildings, homes, and utilities

  1. Smart buildings. Most of today’s large commercial buildings feature sensors that collect data on various systems. For example, the place I work in relies on digital thermostats and automation systems to control air conditioning, lighting, heating, and so on. With the data collected and analyzed from these sensors, owners can control equipment across the building more efficiently, as well as anticipate and troubleshoot issues before they escalate to a phone call, thus increasing tenant comfort, satisfaction, and hopefully retention. Smart building infrastructure, automation systems, and the energy management software that ties this data together are also helping owners cut back on one of their largest operating expenditures—electric and gas utilities—by ensuring that the lighting, heating, and air conditioning systems are running at optimal levels at the right times—not at 11 p.m. on a Saturday evening when the building isn’t occupied.
     
  2. Connected homes. From Nest thermostats to Tesla Powerwalls, the plethora of consumer-based energy products on the market today are enabling a new era of connected, energy-savvy homes. Controlling your home’s temperature from a cell phone, powering your electric car with on-site battery storage, and selling excess solar power back to the grid are no longer utopian ideas à la The Jetsons. They’re here today, bringing with them a wave of new sensors and data. As these innovations continue to take hold, product providers will have an opportunity to use data analytics and new applications to deliver ever-greater value to residential customers—telling you how to optimize your HVAC usage, when to sell electricity back to the grid, and how well your rooftop solar is performing relative to yesterday.
     
  3. Utility networks. Cities, governments, and utility providers around the globe are upgrading grid infrastructure with smarter capabilities to enable smoother operation, superior resilience, and greater value and customer service for rate payers. These investments—driven in part by regulatory environments, increased competition, and the onslaught of distributed energy resources—are opening the door to new streams of sensor data and a greater need for analytical solutions. For example, advanced metering infrastructure (AMI) combined with consumption analytics are allowing utilities to better understand their customers’ behavior and how best to engage with those customers on energy efficiency projects—an important goal for many public utility commissions. Advanced analytics can be deployed on this same AMI network to monitor the health of utility infrastructure and identify fraudulent energy usage.
     

Making sense of sensor data

While sensor and machine data can deliver enormous value and bottom-line benefits, creating an ecosystem of connected solutions and technologies around this data is not always easy. Interoperability issues can arise from disparate networks of sensors and devices. And with massive amounts of data coming online, oftentimes information is thrown out or left to sit in data lakes without further analysis or use. This can prevent companies from reaping the tremendous value that energy IoT data provides.

Fortunately, there is a way to capitalize on the potential of sensor data. The HPE Vertica Analytics Platform is a purpose-built analytics engine designed to handle incredibly large volumes of data, whether at the data center or at the edge of the network.

Its analytic columnar database supports greater data compression, allowing users to query data in environments where speed and performance are critical to gleaning insights. And because HPE Vertica Analytics Platform interacts with a broad ecosystem of solutions—including the HPE Universal IoT Platform, BI, visualization, predictive analytics, data prep, ETL, cloud, open source, security, and other solutions—the potential to derive value from Big Data in the energy world is ever-growing.

To learn more about how the HPE Vertica Analytics Platform can help companies reap the benefits of Big Data, read the white paper, “Capitalize on the untapped potential of sensor data” or attend this session on predictive analytics in HPE Vertica at HPE’s Big Data Conference 2016, August 29-September 1.

Follow @HPE_IoT and @HPE_BigData on Twitter to stay up to date on the latest HPE IoT news.

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