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所在平台: Udemy |
课程主页: https://www.udemy.com/course/aws-greengrass/
课程评论：没有评论
课程名称：全面指导物联网系统运行 - AWS Greengrass！ 课程概述： AWS Greengrass是一个软件平台，允许您以安全的方式在连接设备上运行本地计算、消息传递、数据缓存、同步和机器学习推理能力。使用AWS Greengrass，连接设备能够运行AWS Lambda函数、保持设备数据同步，并在不连接互联网时也能安全地与其他设备通信。得益于AWS Lambda，Greengrass确保您的物联网设备能够快速响应本地事件，并通过Greengrass Core与本地资源互动，在连接不稳定的情况下运行、进行空中更新、降低将物联网数据传输到云端的成本。AWS Greengrass的机器学习推理功能使得在Greengrass Core设备上使用在云中构建和训练的模型进行本地机器学习推理变得简单。 AWS Greengrass便捷地将AWS扩展至设备，使其能够对生成的数据进行本地处理，同时仍然利用云端进行管理、分析和持久存储。借助Greengrass，您可以使用熟悉的编程语言和模型在云中创建和测试设备软件，然后将其部署到设备上。同时，AWS Greengrass可以编程过滤设备数据，仅将必要信息传输回云端。AWS Greengrass利用AWS IoT Core的安全性和访问管理能力，对设备数据在所有连接点进行身份验证和加密，从而确保设备之间以及设备和云之间的通信在没有证明身份的情况下不进行数据交换。 课程收益： - 实时响应本地事件：AWS Greengrass设备可以本地操作生成的数据，从而快速响应事件，同时利用云进行管理和分析。 - 离线操作：即使与云的连接不稳定，AWS Greengrass也能使连接设备正常工作。 - 安全通信：AWS Greengrass对本地和云通信的设备数据进行身份验证和加密，确保数据安全。 - 简化设备编程：利用AWS Lambda编程模型，便于在云中开发代码并无缝部署到设备。 - 降低物联网应用的运行成本：Greengrass可以帮助设置本地数据过滤，减少传输到云的数据量，从而降低成本。 应用案例： - 安全和交通监控：例如，通过AWS Greengrass ML推理，可以在交通摄像头上进行本地预测，优化交通流量。 - 零售和酒店业：商家可在游乐园中使用物体识别模型进行游客计数，提升客户体验。 - 精准农业：Greengrass可帮助农业监测环境变化，提高作物产量和质量。 - 预测工业维护：通过监控传感器数据提前识别设备故障，以提高生产效率。 该课程为学习和运用AWS Greengrass提供了全面的指导，从而帮助用户高效地管理物联网设备并优化其性能。
AWS Greengrass is software that lets you run local compute, messaging, data caching, sync, and ML inference capabilities for connected devices in a secure way. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely - even when not connected to the Internet. Using AWS Lambda, Greengrass ensures your IoT devices can respond quickly to local events, use Lambda functions running on Greengrass Core to interact with local resources, operate with intermittent connections, stay updated with over the air updates, and minimize the cost of transmitting IoT data to the cloud. ML Inference is a feature of AWS Greengrass that makes it easy to perform machine learning inference locally on Greengrass Core devices using models that are built and trained in the cloud. AWS Greengrass seamlessly extends AWS to devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. With Greengrass, you can use familiar languages and programming models to create and test your device software in the cloud, and then deploy it to your devices. AWS Greengrass can be programmed to filter device data and only transmit necessary information back to the cloud. AWS Greengrass authenticates and encrypts device data at all points of connection using the security and access management capabilities of AWS IoT Core. This way, data is never exchanged between devices when they communicate with each other and the cloud, without proven identity. Benefits:Respond to Local Events in Near Real-timeAWS Greengrass devices can act locally on the data they generate so they can respond quickly to local events, while still using the cloud for management, analytics, and durable storage. The local resource access feature allows Lambda functions deployed on Greengrass Core devices to use local device resources like cameras, serial ports, or GPUs so that device applications can quickly access and process local data. Operate OfflineAWS Greengrass lets connected devices operate even with intermittent connectivity to the cloud. Once the device reconnects, Greengrass synchronizes the data on the device with AWS IoT Core, providing seamless functionality regardless of connectivity. Secure CommunicationAWS Greengrass authenticates and encrypts device data for both local and cloud communications, so that data is never exchanged between devices and the cloud without proven identity. Greengrass uses the same security and access management you are familiar with in AWS IoT Core, with mutual device authentication and authorization, and secure connectivity to the cloud Simplified Device Programming with AWS LambdaAWS Greengrass uses the same AWS Lambda programming model you use in the cloud, so you can develop code in the cloud and then deploy it seamlessly to your devices. Greengrass lets you execute Lambda functions locally, reducing the complexity of developing embedded software Reduce the Cost of Running IoT ApplicationsWith AWS Greengrass you can program the device to filter device data locally and only transmit the data you need for your applications to cloud. This reduces the amount of raw data transmitted to the cloud and lowers cost, and increases the quality of the data you send to the cloud so you can achieve rich insight at a lower cost.Use CasesAWS Greengrass ML Inference can be deployed on connected devices like security cameras, traffic cameras, body cameras, and medical imaging equipment to help them make predictions locally. With AWS Greengrass ML Inference, you can deploy and run ML models like facial recognition, object detection, and image density directly on the device. For example, a traffic camera could count bicycles, vehicles, and pedestrians passing through an intersection and detect when traffic signals need to be adjusted in order to optimize traffic flows and keep people safe.Retail and HospitalityRetailers, cruise lines, and amusement parks are investing in IoT applications to provide better customer service. For example, you can run object detection models at amusement parks to keep track of visitor count. Cameras locate the visitors and maintain a running headcount locally without having to send massive amounts of video feed to the cloud, which is often a challenge due to limited internet bandwidth at parks. This solution can predict wait times at popular theme park rides and help improve the customer experience.SecuritySecurity camera manufacturers are looking for new ways to make devices more intelligent and automate their threat detection capabilities. AWS Greengrass ML Inference can help improve the capabilities of security cameras. Greengrass enabled cameras can continuously scan premises to look for a change in the scene, such as an incoming visitor, and send an alert. The cameras are able to quickly perform scene detection analysis locally and send data to the cloud only when required, e.g., for additional analysis to identify whether a visitor is a family member.Precision AgricultureThe agriculture industry is going through two major disruptions. First, the world's population continues to grow causing the demand for food to outweigh the output. Second, climate change is resulting in unpredictable weather conditions, affecting crop yields. AWS Greengrass ML Inference can help transform agriculture practices and deliver new value to customers. Greengrass-powered cameras installed in greenhouses and farms can process images of plants, crops, and data from sensors in the soil to not only detect environmental anomalies such as change in temperature, moisture, and nutrition level, but also trigger alerts.Predictive Industrial MaintenanceAs pricing pressure increases on manufacturers, they are looking for newer ways to help increase operational efficiency on factory floors. Delays in detecting issues on the manufacturing assembly line can lead to a waste of time and resources. AWS Greengrass ML Inference can help you in early detection of faulty equipment and issues on the factory floor. Greengrass-powered industrial gateways can continuously monitor the sensor data (e.g., vibrations, noise-level), predict anomalies, and take relevant actions such as send alerts or shut-off the power to minimize losses.
