📄️ Activity Logs
Records of actions, events, and operations within an IoT system, useful for monitoring, troubleshooting, and auditing purposes.
📄️ Anomaly Detection
The identification of data points, events, or patterns that deviate from the norm, often using machine learning techniques and IoT data to detect potential issues or security threats.
📄️ Azure Container Instances
A Microsoft Azure service that enables running containerized applications without the need for provisioning or managing underlying infrastructure, simplifying the deployment and scaling of IoT solutions.
📄️ Blob Storage
A cloud-based storage service designed to store large amounts of unstructured data, such as text or binary data, which can be useful for storing IoT-generated data like telemetry, logs, and multimedia content.
📄️ Cloud Computing
The delivery of computing services, such as storage, processing, and analytics, over the Internet, allowing IoT systems to leverage shared resources and scale on-demand.
📄️ Cloud IoT
The integration of IoT devices and systems with cloud-based services for data storage, processing, analytics, and management.
📄️ Condition Monitoring
The process of tracking the performance and health of equipment using IoT sensors and devices, enabling early detection of potential issues and optimizing maintenance schedules.
📄️ Context-Aware Computing
The use of IoT sensors, devices, and data to understand the environment and context of a system, enabling adaptive and personalized experiences.
📄️ Data Aggregation
The process of collecting, organizing, and presenting data from multiple sources, often used in IoT applications to generate insights from diverse data sets.
📄️ Data Fusion
The process of integrating data from multiple sources to improve the accuracy, reliability, and completeness of information, often used in IoT applications to enhance decision-making.
📄️ Digital Twins Definition Language (DTDL) Tutorial
Welcome to the DTDL tutorial page. This tutorial is designed to give you a foundational understanding of DTDL — what it is, its benefits, syntax, and how to use it.
📄️ Edge Analytics
The process of analyzing data at the edge of the network, close to the source of data, enabling faster decision-making and reduced data transmission costs.
📄️ Edge Computing
A distributed computing paradigm that brings data processing and analytics closer to the source of data, reducing latency and bandwidth requirements.
📄️ Industrial Control System (ICS)
A system used to manage and control industrial processes, which often incorporates IoT technologies to monitor and control equipment in real-time.
📄️ Message Routing
The process of directing messages from IoT devices to appropriate cloud services or applications, based on predefined rules and filters.
📄️ Over-the-Air (OTA) Updates
The process of remotely updating the software or firmware of IoT devices through wireless communication, improving security and performance.
📄️ Queue Storage
A data storage service that enables IoT applications to store and retrieve messages in a first-in, first-out (FIFO) manner, facilitating communication between distributed components.
📄️ Stream Analytics
A real-time data processing service that enables the analysis of streaming data from IoT devices, providing insights and triggering actions in response to events.
📄️ Table Storage
A NoSQL data storage service designed for storing large amounts of structured, non-relational data, commonly used in IoT systems for handling sensor data, metadata, and configuration settings.
📄️ Telemetry
The process of collecting, transmitting, and analyzing data from remote sensors or devices, often used in IoT applications to monitor and control equipment, systems, or environments.