Hello People. This article discusses about AWS IOT Analytics for IOT applications. AWS IoT Analytics and Amazon Kinesis Data Analytics can stream data in real time to help business teams store and process information.
AWS IoT Analytics is applicable for use cases such as predictive maintenance, business process optimization and predictive fleet management, while Kinesis Data Analytics has a faster response time that benefits industrial monitoring and control applications.
AWS IOT analytics contains built-in AWS IoT Core support, which makes it easy to automatically and securely set up and collect data from a large number of devices. IoT Core integration also makes it easier to associate device data with a specific sensor make and model or associate a collection of sensors with a larger device to pinpoint where data is coming from.
Software engineers can automatically cleanse bad data such as that caused by inaccurate sensor readings as well as enrich data streams with outside sources and automatically store this enriched feed in a time series format using AWS IOT analytics. For example, an organization could combine IoT data from a fleet of trucks with weather data, inventory data and truck maintenance data to alter delivery schedules and generate other cost-saving measures.
On the other hand, Amazon Kinesis Data Analytics is more useful with real-time device monitoring and process control. The service supports millisecond response times, compared to seconds or minutes with AWS IoT Analytics.
Kinesis Data Analytics could be a good fit in industrial monitoring applications. Engineers might want to calculate rolling 10-second temperature averages to detect potential anomalies. This feature could be used to automatically shut down machinery and prevent an accident.
Software engineers can combine AWS IoT Analytics and Kinesis Data Analytics for some IoT applications. In this scenario, IoT Analytics is better suited to analyze data at rest or store data for long-term analysis, while Kinesis Data Analytics could drive real-time algorithms to control equipment or alert equipment operators.
In conclusion, IoT Analytics enables developers to take the raw, unstructured data that IoT devices feed to AWS, and create reports based on that information, a press release said. These reports can be extended further by combining the IoT data with outside data, and can be used with an embedded SQL engine to provide answers about a given data set.
Hope this article about AWS IOT Analytics for IOT applications is useful to you. Please read about Tata power EV charging stations in Andhra Pradesh