People Flow Big-Data Processing

In the world today with high IoT / 5G / AI technologies, the world generations a massive data of people/events, and it is more than ever import to utilize its impact and draw implications effectively. Mobility data (time/ place) plays a vital role to interlink these datasets

Location data

Our everyday devices are the sources for location data such as mobile phones, cars, Wi-Fi, Bluetooth, etc. However, location data that these devices generate is not perfect as-is and contains data noise and fallouts that may affect data computation and analysis.

LocationMind utilizes geospatial data such as land, buildings, roads, railways, and statistical datasets such as population and traffic, to provide its location-related services. The accuracy of such datasets and their maintenance significantly affects the efficiency of analysis by data users. It is also causally related to the flexibility in crisscross interlinking of datasets and data transformations. LocationMind increases the efficacy of data analysis by supporting data cleaning, supplementation, data cleansing, processing, and assist in the development of spatiotemporal datasets and dashboards.

Example of Data Noise and how we correct it.

LocationMind’s xPop Multi-layered Processing Workflow offers continuous processing and system development of location information data for our customers.

Please contact us if any of these keywords interests you:

  • Pre-processing of Location Big Data
  • Procurement of Location Big Data
    (via LocationMind xPop etc.)
  • Continuous monitoring
    using Location Data
  • Analysis that involves
    Location Data and Proprietary Data
    held by clients
  • Edge Computing of Location Data
  • Recording Location Data
    using IoT Devices
    Like smartphones and Sensors