Robots are coming! Build IoT apps with Watson, Swift, and Node-RED Cognitive Class Exam Quiz Answers

Clear My Certification January 15, 2024 Cognitive Class Leave a comment 158 Views

Enroll Here: Robots are coming! Build IoT apps with Watson, Swift, and Node-RED Cognitive Class Exam Quiz Answers

Robots are coming! Build IoT apps with Watson, Swift, and Node-RED Cognitive Class Certification Answers

Lab 1: Read Temperature Data from an IoT Sensor Quiz Answers – Cognitive Class

Question 1: In Lab 1, what is the main purpose of the Internet of Things Platform Starter?

To provide a boilerplate application in Node-RED
To facilitate communication between the Node-RED instance running on the Raspberry Pi and the instance running on IBM Cloud
To send data from an iOS device to Twitter
To create a Cloudant database

Question 2: In Lab 1, where exactly does the Swift UI get the temperature data from?

Directly from the temperature senson device
From a node in the Node-RED flow
From the Cloudant database
From the IoT QuickStart

Question 3: What imported library is required for you to do CRUD operations on the Cloudant database in IBM Cloud?

SwiftDBCloudant
CloudantSwift
SwiftyDB
SwiftCloudant

Question 4: In Lab 1, why did you need two Node-RED flows?

To get sensor data (flow 1) and then to send it to IBM Cloud (flow 2)
To set up a Cloudant database (flow 1) and then send it IBM Cloud (flow 2)
To get sensor data (flow 1) and then send it to the IoT Platform QuickStart (flow 2)
None of these

Question 5: In which Node-RED node do you initially enter a device ID? In this lab, the device ID is from the virtual temperature sensor.

IBM IoT App Out
msg.payload
IBM IoT App In
GetCPUtemp

Lab 2: Add a Camera and Analyze Images Quiz Answers – Cognitive Class

Question 1: How is Watson Visual Recognition used by the Raspberry Pi in an IoT environment?

Pictures taken by the Raspberry Pi camera are sent in bulk to the cloud and matched against existing pictures.
Pictures taken by the Raspberry Pi camera are matched against existing pictures on the Raspberry Pi. The result is communicated to the cloud.
Single pictures taken by the Raspberry Pi camera are sent to the cloud and processed by the deep learning network trained on existing pictures.
Pictures taken by the Raspberry Pi camera are minimized on the Raspberry Pi before being sent to the cloud for comparison with existing pictures.

Question 2: The Visual Recognition service uses machine learning to recognize and classify visual content.

True
False

Question 3: MQTT cannot be used to pass data through firewalls.

True
False

Question 4: What action does the following Swift code perform?

DispatchQueue.main.asyncAfter(deadline: .now() + .seconds(10), execute: {

// Put your code which should be executed with a delay here

NSLog(“Read doc: 10 sec”)

self.imageFromDb.image = self.fetchedImage as UIImage

})

Updates the Cloudant database with a new picture
Shows a picture on a mobile device
Creates buttons in your mobile UI
Sends a picture to the Visual Recognition service

Question 5: In Node-RED, output nodes have the logo on the left side of the node.

True
False

Lab 3: Connect Your App to an iRobot and Smartphone Quiz Answers – Cognitive Class

Question 1: Which one of the following SDKs helps to simplify how you use cognitive services with Swift applications?

Text-to-speech-swift
Watson-Developer-Cloud SDK for iOS
SwiftyJSON SDK
IBM Cloud Services SDK for iOS

Question 2: What’s the purpose of the WeatherData.swift file?

Adds the encoding for the network
Connects the Text to Speech service to the iRobot
Manages the connectivity to the Text to Speech service
Manages the connectivity to the Weather Company Data service

Question 3: The Watson IoT Platform starter automatically deploys and connects which of these services. Select all that apply.

Watson IoT Platform
Weather Company Data service
IBM SDK for Node.js for IBM Cloud
IBM Cloudant for IBM Cloud

Question 4: To manipulate JSON, you added which framework to the XCode project?

SpeechToTextV1.framework
RestKit.framework
SwiftyJSON.framework
BMSCore.framework

Question 5: What additional data can you find in the Weather Data JSON?

Conditions for playing golf
Conditions for skating
Conditions for hiking
Conditions for swimming
Conditions for running

Robots are coming! Build IoT apps with Watson, Swift, and Node-RED Final Exam Answers – Cognitive Class

Question 1: Which of the following data types can be be sent from an IoT sensor to the cloud for further processing? Select all that apply.

Temperature
Humidity
Air pressure
Seismometer data
Text

Question 2: What is the lightweight protocol that is used for communication between a Raspberry Pi device and a cloud application?

TCP/IP
HTTP
MQTT
MSP

Question 3: Which Watson services can you use to build a voice user interface to access IoT devices?

Speech to Text
Real-time Audio conversion
Text to Speech
Voice routing over the Internet

Question 4: You typically need to install a node package to get Cloudant database nodes in Node-RED.

True
False

Question 5: How does BM Watson Visual Recognition determine what’s in an image?

By analyzing the file names of images
By deciding what categories the image and the parts of an image fall into
By reading what users post on social media about an image
By querying the user who ted the image

Question 6: In this course, how did you connect the Raspberry PI to the iRobot?

MQTT
The iRobot serial port
HTTP
ICMP

Question 7: IBM Cloudant is an example of which of the following service types? Select all that apply.

MBaaS
PaaS
SaaS
DBaaS

Question 8: What action does the following code perform?

iotfSession.send(BEEP_MSG.data(using: String.Encoding.utf8, allowLossyConversion: false),

topic: CMD_TOPIC,

qos: MQTTQosLevel.exactlyOnce,

retain: false)

Sends a dock command to the iRobot
Specifies what encoding to use
Sends a command over an MQTT connection
Sends a command to a smartphone

Question 9: What method can you use to extend the functionality of Raspbian Jessie?

npm
Configure it with apt-get commands
Download nodes from the Node-RED community
CocoaPods

Question 10: You can store pictures from a camera or from the Internet by using a Cloudant database.

True
False

Introduction to Robots are coming! Build IoT apps with Watson, Swift, and Node-RED

Building Internet of Things (IoT) applications using Watson, Swift, and Node-RED involves combining different technologies to create a comprehensive solution. Below are the steps you can follow to build IoT apps with these technologies:

1. Define the IoT Use Case:

Identify the specific use case for your IoT application. Define what kind of data you want to collect from IoT devices and what insights or actions you want to derive from that data.

2. Select IoT Devices:

Choose the IoT devices or sensors that are appropriate for your use case. Ensure that these devices can communicate data to your IoT application.

3. Setup Node-RED:

Node-RED is a visual programming tool for wiring together IoT devices, APIs, and online services. Install and set up Node-RED on a server or a device that will act as a gateway for your IoT devices.

4. Connect IoT Devices to Node-RED:

Use the appropriate protocols (e.g., MQTT, HTTP) to connect your IoT devices to Node-RED. Node-RED provides nodes (blocks) that make it easy to interface with various IoT devices.

5. Integrate Watson IoT Platform:

IBM Watson IoT Platform helps you securely connect and manage IoT devices. Integrate the Watson IoT Platform with Node-RED to leverage its features such as device management, real-time data analysis, and insights.

6. Develop Swift Application:

If you’re developing a mobile application, use Swift for iOS app development. Ensure that your Swift app can communicate with Node-RED or the Watson IoT Platform to send and receive data.

7. Implement Data Processing and Analytics:

Use Node-RED to process and analyze the data coming from IoT devices. You can integrate Watson services, such as Watson Machine Learning or Watson Studio, for more advanced analytics and insights.

8. Implement Node-RED Flows:

Create Node-RED flows to define how data should flow between devices, services, and applications. Use the visual programming interface to set up the logic for your IoT application.

9. Implement Cloud Services:

Utilize cloud services, such as IBM Cloud or other cloud providers, to host and scale your IoT application. Ensure that your cloud infrastructure can handle the data volume and provide high availability.

10. Implement Security Measures:

Implement security measures at every level of your IoT application. Secure communication between devices and the backend, and use proper authentication and authorization mechanisms.

11. Test and Debug:

Test your IoT application thoroughly to ensure that data flows correctly, and devices are communicating as expected. Debug and optimize your Node-RED flows and Swift application.

12. Deploy and Monitor:

Deploy your IoT application to production, and set up monitoring tools to keep track of device status, data flow, and system performance.

13. Iterate and Improve:

Continuously iterate on your IoT application based on user feedback and changing requirements. Use insights gained from analytics to improve the efficiency and functionality of your application.

By combining the capabilities of Watson, Swift, and Node-RED, you can create a robust and scalable IoT application that efficiently processes data from devices, performs analytics, and provides valuable insights.