Sensor Analytics

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Solutions Brief:
Unlocking the Massive Potential of Sensor Data With the HP Vertica Analytics Platform

Learn How HP helps organizations, particularly intelligent device manufacturers, manage and analyze massive volumes of sensor data to predict and prevent operational issues and reduce service costs, improve customer satisfaction by extending operational uptime, and bring revenue-generating machine to machine (M2M) solutions to market. >>Learn more

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Unlock the Massive Potential of Sensor Data

In the coming years, data generated by sensors and machine-to-machine (M2M) communication, or the Internet of Things, will fill the storage systems of data centers across a wide range of industries. In fact, IDC forecasts that machine-generated data will increase to 42% of all data by 2020, up from 11% in 2005.

For years, people have been talking about the potential impacts of this data deluge from the Internet of Things. Today, the talk is shifting to the opportunity to use sensor data to drive new business models. Data-driven business models are already happening across a wide range of industries—from insurance and banking to manufacturing and medical products. The future will bring much more of this.

Across a wide range of industries, organizations are running analytics on sensor data to enable new value-added products, services, and business processes. All of these use cases are driven by analyzing petabytes of data collected from sensors and M2M communications.

  • Fleet management
    Sensor data from delivery trucks is helping businesses schedule preventive maintenance before mechanical issues can disrupt fleet operations.
  • Healthcare sensing
    Biosensors are now used to enable better and more efficient patient care across a wide range of healthcare operations, including telemedicine, telehealth, and mobile health.
  • Product monitoring
    Manufacturers use sensor-data analytics to monitor the health and performance of their products and to work proactively to address service and maintenance issues before they lead to product downtime.
  • Predictive maintenance
    Airlines use data from airplane sensors to proactively manage maintenance, improve reliability, reduce unplanned service work, and mitigate risk.
  • Safety compliance
    Energy exploration companies analyze sensor data collected from oil drilling platforms to verify compliance with safety requirements and guide proactive steps to improve safety.
  • Smart appliances
    Manufacturers use data from smart appliances to address a wide range of consumer needs—everything from replenishing groceries in a refrigerator to optimizing the use of washing machines and stoves.
  • Smart buildings
    Facilities personnel use monitors to gather data on building systems, including heating, ventilation, and air conditioning (HVAC) equipment, to enable alarm monitoring and active notifications, proactive maintenance, and optimization of systems.
  • Smart drilling
    In the oil and gas industry, seismic exploration data is helping companies find profitable locations with less experimental drilling, lowering both operational cost and environmental impact.
  • Smart grids
    Forward-looking cities and governments are upgrading electrical-grid infrastructure with smarter capabilities to enable smoother operation and tighter security.
  • Smart meters
    Utilities are deploying digital, networked meters to systematically feed analytics tools and Web-based portals with consumption data.
  • Usage-based insurance
    Insurance companies use data generated from sensors in automobiles to offer drivers rates based on the amount of driving they do, their driving habits, and even where they drive and park.