Indoor location tracking analytics
TensorFlow™ is an open-source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
R programming language on a GPU-enabled server, the framework is used extensively by our team to build data models for forecasting and predictions. Our indoor location tracking analytics solutions are being deployed in hospitals (inventory, patient workflow, preventive maintenance, business impact) and smart farming (pH values, soil moisture), and Warehousing (Truck arrivals, cargo carried, accidents, driver behavior)
Watch this space for some exciting machine learning projects we are executing with deep learning and business analytics tools, integrating real-time sensor data for Indoor positioning analytics in a greenhouse farm environment, patient tracking, warehouse forklift tracking, etc
Call or contact us for more information on how to deliver indoor location tracking analytics using ML / BA on your organization’s data. Learn about BA forecasting models using R