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.
The integration of ________ technology marked a significant evolution in the capabilities of IoT devices.
- 5G
- Artificial Intelligence
- Augmented Reality
- Quantum Computing
The integration of "5G" technology marked a significant evolution in the capabilities of IoT devices. The high-speed, low-latency nature of 5G networks enables faster and more efficient communication between IoT devices, paving the way for new applications and functionalities.
A company is planning to deploy IoT devices across its infrastructure. Before doing so, it seeks certification from a recognized body to ensure the devices meet security standards. They are likely seeking certification from:
- Federal Communications Commission (FCC)
- IEEE Standards Association
- ISO/IEC 27001
- Wi-Fi Alliance
ISO/IEC 27001 is a widely recognized standard for information security management systems. Seeking certification from this body indicates a commitment to maintaining high-security standards for IoT devices.
In a futuristic city, residents are alerted about environmental conditions like air quality through their smartphones. This IoT application can be categorized under:
- Environmental Monitoring
- Mobile Gaming
- Smart Cities
- Wearable Technology
The given scenario falls under the Smart Cities category of IoT. It involves using sensors and data to monitor and improve the quality of life in urban areas. This specific application focuses on environmental monitoring, ensuring that residents are informed about air quality, which is a critical aspect of urban well-being.
The shift from centralized cloud computing to edge computing in IoT was primarily due to:
- The need for more powerful data centers.
- The increased demand for low-latency processing.
- Decreased security concerns.
- Lower energy consumption.
The primary driver for the shift from centralized cloud computing to edge computing in IoT is the increased demand for low-latency processing. In many IoT applications, such as autonomous vehicles and industrial automation, real-time or near-real-time data processing is critical, and edge computing helps achieve this by processing data closer to the source.
In a modern smart home, the resident wants the lights to automatically adjust based on the time of day and presence in the room. The system would likely involve:
- Blockchain technology
- Neural networks
- Home automation and occupancy sensors
- Augmented reality (AR)
To achieve the automatic adjustment of lights in a modern smart home based on the time of day and presence in the room, the system would likely involve home automation and occupancy sensors. These sensors detect motion and light levels, enabling the smart home system to control lighting based on occupancy and time, enhancing energy efficiency and convenience.