In the early 1990s, a company wanted to monitor its supply chain more effectively. This led to the development of an early IoT concept using which technology?
- Bluetooth
- RFID (Radio-Frequency Identification)
- Wireless Sensor Networks
- Zigbee
In the early 1990s, the development of an early IoT concept for supply chain monitoring was mainly based on RFID technology. RFID allowed the tracking of products or assets using radio waves, making it a crucial technology for early IoT implementations.
The primary distinction between IoT security standards and regulatory compliance is:
- Focus on implementation details
- Legal requirements vs. best practices
- Network architecture vs. data integrity
- Technical specifications vs. encryption
IoT security standards primarily involve best practices and technical specifications for securing IoT devices and data, while regulatory compliance pertains to legal requirements set by authorities.
In the context of IoT projects, the study of successful implementations to understand best practices is referred to as ________.
- Best Practice Evaluation
- Case Analysis
- Lessons Learned
- Success Studies
In IoT projects, the study of successful implementations to understand best practices is often referred to as "Lessons Learned." This involves analyzing successful cases to identify strategies, approaches, and practices that can be applied to future projects.
Which of the following is a primary concern when it comes to IoT data security?
- Data compression techniques
- Data encryption and decryption
- Data transmission latency
- Unauthorized access and data breaches
A primary concern in IoT data security is unauthorized access and data breaches. IoT devices often handle sensitive information, making them targets for cyberattacks. Ensuring that data remains secure and protected from unauthorized access is a critical consideration.
A city is using IoT sensors combined with AI to manage and optimize traffic flow. The sensors collect data, and the AI model predicts traffic congestion. This is an example of:
- AI for Entertainment
- AI for Social Media Analytics
- IoT for Environmental Monitoring
- IoT for Smart Traffic Management
This scenario exemplifies the use of IoT (Internet of Things) for Smart Traffic Management, where sensors collect real-time data and AI is applied to predict traffic congestion and optimize traffic flow.
Kevin Ashton, who coined the term IoT, related it primarily to:
- Connecting electronic devices
- Connecting household appliances
- Connecting industrial machinery
- Connecting physical objects to the Internet
Kevin Ashton, who coined the term "Internet of Things," related it primarily to the idea of connecting physical objects to the Internet to enable them to communicate and share data. His vision laid the groundwork for the IoT we know today.
________ is a lightweight OS designed specifically for the Internet of Things, often used in resource-constrained devices.
- Mbed OS
- Ubuntu Linux
- Windows 10
- macOS
Mbed OS is a lightweight and open-source operating system designed for IoT devices, particularly those with limited resources. Windows 10, Ubuntu Linux, and macOS are not specifically tailored for IoT and are typically used in larger systems.
In smart homes, when you use voice commands to control lighting, this is an instance of ________ communication.
- IoT
- Machine
- Voice
- Wireless
In smart homes, when you use voice commands to control lighting, this is an instance of "Voice" communication. It's a communication method where you are using your voice to interact with the home automation system to control various devices like lighting, thermostats, and more.
A case study discusses a farming project where soil moisture sensors were used in conjunction with AI to optimize irrigation. The integration of AI in this scenario primarily serves to:
- Automate Harvesting
- Enhance Water Efficiency
- Improve Soil Fertility
- Increase Crop Yields
In the context of agriculture, the integration of AI with soil moisture sensors primarily serves to enhance water efficiency, ensuring that irrigation is applied precisely where and when it's needed, conserving water resources.
An agriculture firm is using drones to capture field images. To process this data immediately without sending it to a central cloud, the firm should use:
- Blockchain technology
- Cloud-based data processing
- Edge computing
- Hadoop cluster
In an agriculture scenario where immediate data processing is needed, edge computing is the suitable choice. Edge computing processes data locally (in the drones) without the need to send it to a central cloud, reducing latency and improving efficiency for real-time applications.