DATABERG
Datumize Data Collector (DDC) ensures smart data generation by capturing the right data stream from any data source and processing it in real-time, utilizing Edge Computing to extract valuable information, and finally producing actionable results for the organization.
One of the data sources that Datumize Data Collector (DDC) taps into is the real-time status information of Wi-Fi networks. This will provide valuable data especially for companies in the logistics, hospitality and retail sectors.
Wi-Fi is a family of radio technologies universally used for wireless networking of devices. The first non-wired connectivity between computers was established back in 1971, and since then the IEEE 802.11 protocols have evolved, becoming the de-facto standard of wireless short-range connectivity of the Internet era. Wi-Fi is a ubiquitous technology that is present in almost every facility today, as its availability has become a feature that the customers expect.
But from the perspective of data analytics, the value hidden in Wi-Fi networks is beyond the pure wireless networking connectivity: each Wi-Fi Access Point (the device that is used to connect a wireless device to the supporting wired network) is already generating a wide variety of data that remains poorly explored. The Access Point contains relevant information on the endpoint device (identified by a MAC address), including the signal strength and other valuable technical metrics. These Dark Data can be used to deliver mobility intelligence to companies, such as locating devices and understanding their movement patterns, whether they are the smartphones of hotel clients or trucks in a warehouse.
Collecting Wi-Fi data and creating motion intelligence
Datumize Data Collector (DDC) is a lightweight and high-performance software for data ingestion, capable of tapping into the data from Wi-Fi technologies via active polling techniques.
Thanks to the Mobility Assembler Connector, Datumize Data Collector (DDC) is able to perform the first layer of motion data enrichment, consisting of trilateration and device fingerprinting. The functionality can be expanded with a more advanced Artificial Intelligence (AI) layer, utilizing heuristics and mathematical algorithms that increase the accuracy of the resulting path information for various tracking purposes.
The resulting structured and prepared geospatial data can then be further expanded by joining it with third-party business-specific data, resulting in valuable operational metrics. Good example is the application of Datumize Data Collector (DDC) in warehouses, where we join the geospatial data with data from a Warehouse Management System. The resulting combination allows the tracking of events in a warehouse on a mission level.
Another user case is the tracking of hotel guests, giving valuable insights on the use of various hotel amenities, restaurant peak times, etc. The result of such information is deep understanding of guests' behavior, which can be used to plan resource allocations and productivity enhancements.
