The path to machine learning and personalization requires that some computing occur at the edge of the network. In fact, Gartner is forecasting that companies will generate up to 75 percent of their data outside a traditional data center within the next six years.1 Privacy is one big reason for the need for edge computing. As more devices become interconnected, it is much easier to protect data at the edge than when routed through a central server.

Another driver for edge computing is the need for real-time decision-making. Processing data through the cloud can take 150 milliseconds or longer, whereas edge computing can process data locally in just 5 to 10 milliseconds.2 In applications where instantaneous decisions are required, such as helping an autonomous car detect a pedestrian, or identifying a suspect in a video surveillance system, time matters.

Edge computing means that there will be billions of sensors providing data to make local decisions. But these decisions cannot happen without ubiquitous connectivity and plenty of bandwidth.

While edge computing will play a significant role in enabling machine learning, so too will cloud computing. The ideal solution, then, is a distributed approach that leverages the best of both the cloud and edge. The edge can keep personal data local, enable real-time responses, and provide cost-efficiencies by not requiring centralization of all data. Meanwhile, the cloud can provide device access to an infinite amount of information allowing for better decision-making. It can also widely share this information to multiple devices.

To help product developers create sophisticated, secure, and reliable IoT edge products today that are built for the future, Cypress (now an Infineon Technologies company) has unveiled IoT-AdvantEdge™ solutions. These solutions include connectivity devices and microcontrollers, software, tools and support, and capabilities from ecosystem partners to slash development complexity by solving eight critical IoT design problems: Connectivity, Security, HMI, Low Power, Ease-of-Use, Integration, Cloud, and Monetization.

IoT-AdvantEdge introduces a multifaceted approach to IoT product design that includes devices, software, tools and support, and ecosystem solutions. Devices comprise a unique portfolio of secure microcontrollers, and best-in-class Wi-Fi®, Bluetooth®, and BLE devices that work in concert to support a broad range of IoT product requirements from battery-operated cameras to healthcare products.

From a software perspective, Cypress’ ModusToolbox® development toolchain dramatically simplifies the creation of Wi-Fi and Bluetooth/BLE IoT products with RTOS system MCUs including PSoC®. ModusToolbox includes middleware that connects products to leading cloud-software platforms or proprietary cloud services that reside on either a public or private cloud infrastructure.

In the area of tools and support, IoT-AdvantEdge offers a comprehensive set of tools, including low-power assist, multi-radio smart coexistence, secure authentication, and over-the-air updates. It also includes the Cirrent IoT Network Intelligence (INI) platform that delivers unprecedented insights into connectivity, networking, and other product-performance parameters for fleets of products in the field. Additionally, the IoT-AdvantEdge ecosystem offers pre-integrated capabilities from a broad range of partners – including cloud service providers, application-specific semiconductor products, and applications developers – to help companies bring their IoT products to market faster.

Since introducing IoT-AdvantEdge, Cypress has announced several new IoT products and resources, including new microcontrollers, new development kits, a new software update, and new IoT web resources, such as the IoT Developer Zone on Cypress’ developer community, and a new IoT-AdvantEdge webinar series. For more information about IoT-AdvantEdge, please visit www.cypress.com/iot-advantedge.