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Are microservices about to revolutionize the Internet of Things?
| August 15, 2018
Apache Design, an ANSYS subsidiary, enables simulation-driven IC and electronic systems design by providing advanced chip-level power analysis...
Article | April 14, 2020
The survey data I’m referring to comes from a study conducted by the Eclipse Foundation about the adoption of commercial Internet of Things (IoT) technology. The aim of the study was to get a better understanding of the IoT industry landscape by identifying the requirements, priorities, and challenges faced by organizations deploying and using commercial IoT technologies. More than 350 respondents from multiple industries responded, with about a quarter of respondents coming from industrial production businesses. While this survey was not solely focused on the manufacturing and processing industries, its results reflect the general business community’s IoT adoption at the end of 2019. As such, it is a pre-COVID-19 snapshot of IoT adoption.
Scaling Industrial IoT (IIoT) solutions requires a DevOps organization that can manage increased software and hardware complexity in terms of capability, capacity and footprint. DevOps is derived from Development and Operations and is one of the buzz words for ICT companies. Often it is the amalgamation of Software Developers from R&D and senior engineers from Operations into a new organization. Startups are faced with the challenge of how to quickly create a functioning DevOps organization that can scale with rapid growth. In this article, we will deal with the keys for success to scale software solutions with using an example of an Industrial IoT solution. We will look at how DevOps should function and discuss the important principles for software development, tools and operations.
An integrated Azure IoT solution provides the necessary software, hardware, and cloud services that businesses need to rapidly launch IoT initiatives and quickly realize business value. Using software-based intelligence pre-loaded onto Cisco IoT network devices, telemetry data pipelines from industry-standard protocols, like OPC-Unified Architecture (OPC-UA) and Modbus, can be easily established using a UI directly into Azure IoT Hub. Services, like Microsoft Azure Stream Analytics, Microsoft Azure Machine Learning, and Microsoft Azure Notification Hub services, can be used to build IoT applications for the enterprise. Additional telemetry processing is also supported by Cisco through local scripts developed in Microsoft Visual Studio, where filtered data can also be uploaded directly into Azure IoT Hub. This collaboration provides customers with a fully integrated solution that will give access to design tools, global connectivity, advance analytics, and cognitive services for analyzing IoT data.
Modern cars have dozens of computers on board, and they’re not just for running GPS or playing music. Computers monitor and control nearly every system on your vehicle, including steering, brakes, and the engine itself. This is why automotive cyber security is essential.
If a vehicle’s computer systems aren’t properly protected, hackers can steal data or even take control of the vehicle. As you can imagine, that makes automotive cyber security a major concern for consumers, auto companies, and OEMs alike. But what is there to know about automotive cyber security? We’ll explore what cybersecurity in the automotive industry entails and what the biggest threats are to automotive IoT and connected vehicles. We’ll also share some insights from a recent webinar by Sectigo and Mentor Graphics on how to protect connected vehicles from emerging cybersecurity threats.
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