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    11 Revolutionary Advances in Wireless Tech in 2016

    By
    Chris Preimesberger
    -
    November 11, 2016
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      111 Revolutionary Advances in Wireless Tech in 2016

      1 - 11 Revolutionary Advances in Wireless Tech in 2016

      The industry is seeing more than an incremental gain in wireless capability and user-friendliness this year due to vastly improved system architectures and software.

      2Microservice Architectures Speed Up Change Management

      2 - Microservice Architectures Speed Up Change Management

      New microservices cloud architectures bring software-as-a-service (SaaS) agility to wireless, enabling on-demand network upgrades and patches within minutes. In addition, modern cloud elements, such as Spark and Kafka, are being used for machine learning, automation and high-speed messaging for simpler wireless operations and greater scale.

      3New Platforms Collecting More State Data

      3 - New Platforms Collecting More State Data

      New wireless platforms collect state information from every mobile device in real time so that administrators can view wireless coverage, throughput and other network characteristics from the user’s point of view.

      4On-Site Packet Sniffing a Thing of the Past

      4 - On-Site Packet Sniffing a Thing of the Past

      Dynamic packet capture starts collecting data when an anomaly is detected and stores it in the cloud for easy analysis. This eliminates the need to send tech people on site with packet sniffers.

      5Knowing the State of Users at Any Given Time

      5 - Knowing the State of Users at Any Given Time

      Capturing radio frequency (RF) packets from every device and storing them in the cloud enables administrators to see exactly what the state of a user was at any point in time.

      6More Data Stored for Service-Level Agreements

      6 - More Data Stored for Service-Level Agreements

      Wireless platforms now track connection times, roaming, coverage, capacity throughput and other service-level metrics in real time to ensure users have a great wireless experience.

      7Better Insight for Predictive Analytics

      7 - Better Insight for Predictive Analytics

      Machine learning tracks RF behavior, device characteristics and user patterns to proactively provide recommendations that avoid potential problems.

      8Location Information Much More Accurate

      8 - Location Information Much More Accurate

      New enterprise-grade access points have directional Bluetooth Low Energy (BLE) antenna arrays that deliver unprecedented location accuracy of from 1 to 3 meters.

      9Analytics Takes Into Account All Kinds of Devices

      9 - Analytics Takes Into Account All Kinds of Devices

      Machine learning takes into account the unique characteristics of every mobile device (including iOS, Android, Windows and Linux) to deliver a consistent experience across all wireless users.

      10Bluetooth Site Surveys Will Go Away

      10 - Bluetooth Site Surveys Will Go Away

      Real-time location calibration eliminates the need for expensive and time-consuming Bluetooth Low Energy (BLE) site surveys.

      11Physical Beacons Take a Back Seat

      11 - Physical Beacons Take a Back Seat

      Virtual beacons eliminate many of the hassles of physical beacons, such as deployment, relocation, calibration and battery replacement. This makes location-based services such as wayfinding, proximity messaging and asset tracking more affordable and easier to deploy.

      12Convergence of Services, Analytics Becoming More Common

      12 - Convergence of Services, Analytics Becoming More Common

      Enterprise-grade WiFi, Bluetooth Low Energy (BLE) and IoT services and analytics are now being converged onto single wireless platforms.

      PrevNext

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