This appliance enables competitive advantage with respect to performance, scalability, efficiency and cost-savings. The two-fold nature of the appliance makes it appealing to a broad audience of application providers. The success stories include Vodafone Automotive, leader of the automotive market with a vast amount of data collected nowadays on vehicles and later processed via analytics techniques to infer valuable information.
This appliance tackles a hot problem in the automotive sector: the identification of the number of drivers of a specific vehicle. To this end, the IoT appliance provides a turnkey implementation of a data analytics workflow specifically designed to accurately perform this analysis. The analysis employs a set of raw data collected by the devices installed on the vehicles and it is composed of two main steps:
1. Raw data gets aggregated in a set of features aimed at characterizing the driving style;
2. The number of drivers is identified by the number of clusters found in the aggregated data by a high dimensional clustering method provided by the appliance itself.
You can choose from a wide range of modules forming a heterogeneous cluster. These may be microservers with high-performance x86 or ARM64 as well as low-power ARM processors with the latter also providing GPU computing capabilities. In addition to the CPU-based microservers, FPGAs are available for specialized applications. PCIe extension cards are also supported for even further flexibility.
X86_64 multi-core CPUs
ARM multi-core CPUs
GPU (to be evaluated)
Altera Stratix 10 SX Series FPGA for SEEs
Greatly efficient and with lower cost.
3 Carriers
9 High-Performance Microservers
48 Low-Power Microservers
Ready for the most demanding challenges.
9 Carriers
27 High-Performance Microservers
144 Low-Power Microservers
The most powerful option.
15 Carriers
45 High-Performance Microservers
240 Low-Power Microservers