This white paper introduces Advantech Edge Intelligence Server (EIS) for Internet of Things that enables connectivity, data manageability and analytics in the edge. The EIS includes software packages, core technology, IoT development tools, pre-configured WISE-PaaS software services, plus the flexibility to add more software modules from the WISE-PaaS marketplace. With it, you can build and launch innovative IoT applications and offer easy-integration solutions.
As we know, the IoT has enormous potential. But its evolution has been affected by product development challenges, such as rapidly changing requirements, and a variety of hardware/software technologies and applications. Customers encounter the following pain points in developing an IoT product:
Developing an IoT product usually requires solving problems with sensors, connectivity, security, the cloud, storage, device maintenance, edge/cloud analytics, system integration, device hardware, application development, and so on. One of the first challenges that many companies face is how to migrate to an IoT application while balancing design time, time-to-market, and risk.
IoT data can be large in terms of volume and the applications typically have real-time requirements. Transmitting massive amounts of raw data over a network puts a load on network resources. In some cases, it is much more efficient to process data near its source and send only the valuable fraction over the network to a cloud center. Edge computing is a distributed information technology (IT) architecture in which client data is processed at the periphery of the network, as close to the originating source as possible. Time-sensitive data in edge computing may be processed at the point of origin by an intelligent device or sent to an intermediary server located in close geographical proximity to the client. Data that is less time sensitive is sent to the cloud for historical analysis, big data analytics, and long-term storage.
Advantech EIS adopts edge computing architecture for its IoT solution. EIS enables local IoT networks to perform edge intelligence to maximise energy efficiency, reduce privacy threats, promote easy implementation and modularisation, and minimise latencies.