The internet of things can benefit a wide range of organizations. But IoT systems require professionals who know their way around the technology and understand what it takes to plan, deploy and maintain an IoT system.
When interviewing individuals for these positions, IT leaders and other decision-makers must assess a candidate’s skill levels and ability to comprehend fundamental IoT concepts. They must ask the right IoT interview questions of prospective employees and know what to look for in the answers.
Here are the 30 top interview questions and answers to help with this assessment. These questions can help organizations in need of IoT talent determine whether an individual has the knowledge necessary to meet the demands of the internet of things.
IoT refers to the internet of things. It is a system of interrelated physical devices that are each assigned a unique identifier. IoT extends internet connectivity beyond traditional platforms, such as PCs, laptops and mobile phones.
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IoT devices can transfer data over a network without requiring human interaction. The devices contain embedded systems that can perform different types of operations, such as collecting information about the surrounding environment, transmitting data over a network, responding to remote commands or carrying out actions based on the collected data. IoT devices can include wearables, implants, vehicles, machinery, smartphones, appliances, computing systems or any other device that can be uniquely identified, transfer data and participate in a network.
A wide range of industries can benefit from IoT, including healthcare, agriculture, manufacturing, automotive, public transportation, utilities and energy, environmental, smart cities, smart homes and consumer devices.
IoT benefits the healthcare industry — often through what is called the internet of medical things — in multiple ways, including the following:
A smart city is an urban area that uses IoT technologies to connect city services and enhance their delivery. Smart cities can help reduce crime, optimize public transportation, improve air quality, streamline traffic flow, lower energy use, manage infrastructure, reduce health risks, simplify parking, manage utilities and improve a variety of other processes. Using sensor-driven data collection, the smart city can orchestrate and automate a wide range of services, while reducing costs and making those services easier to access for more people.
Implementing a smart city takes more than just spreading IoT devices around. The city needs a comprehensive infrastructure for deploying and maintaining those devices, as well as for processing, analyzing and storing the data. The system requires sophisticated applications that incorporate advanced technologies, such as artificial intelligence (AI) and predictive analytics. The system must also address security and privacy concerns, as well as interoperability issues that might arise. Not surprisingly, such an effort can take significant time and money, yet the benefits of a smart city could be well worth the effort for the municipality that can make it work.
The IoT architecture consists of the following components:
There are other ways to categorize IoT architecture. For example, treat data processing and storage platforms as a single component, or the break the data processing platform into multiple components, such as hardware and software.
An embedded system is a combination of hardware, software and firmware that’s configured for a specific purpose. It’s essentially a small computer that can be embedded in mechanical or electrical systems, such as automobiles, industrial equipment, medical devices, smart speakers or digital watches. An embedded system might be programmable or have fixed functionality.
It’s generally made up of a processor, memory, power supply and communication ports and includes the software necessary to carry out operations. Some embedded systems might also run a lightweight OS, such as a stripped-down version of Linux.
An embedded system uses communication ports to transmit data from its processor to a peripheral device, which might be a gateway, central data processing platform or another embedded system. The processor might be a microprocessor or a microcontroller, which is a microprocessor that includes integrated memory and peripheral interfaces. To interpret the collected data, the processor uses specialized software stored in memory.
Embedded systems can vary significantly between IoT devices in terms of complexity and function, but they all provide the capacity to process and transmit data.
An embedded system can include any of the following types of hardware components:
An embedded system might comprise multiple sensors and actuators. For example, a system might include several sensors that gather environmental information, which is converted and sent to the processor. Once processed, the data is converted again and sent on to several actuators, which carry out prescribed actions.
A sensor is a physical object that detects and responds to input from its surrounding environment, essentially reading the environment for information. For example, a sensor that measures temperatures within a piece of heavy machinery detects and responds to the temperature within that machinery, as opposed to registering the outside temperature. The information that a sensor gathers is typically transmitted electronically to other components in an embedded system, where it is converted and processed as necessary.
The IoT industry supports many types of sensors, including those that can measure light, heat, motion, moisture, temperature, pressure, proximity, smoke, chemicals, air quality or other environmental conditions. Some IoT devices contain multiple sensors to capture a mix of data. For example, an office building might include smart thermostats that track both temperature and motion. That way, if no one is in the room, the thermostat automatically lowers the heat.
A sensor is different from an actuator, which responds to the data the sensor generates.
Many sensors are available for agriculture, including the following:
A thermocouple sensor is a common type of sensor that measures temperature. The sensor includes two dissimilar electrical metal conductors joined at one end to form an electrical junction, which is where the temperature is measured. The two metal conductors produce a small voltage that can be interpreted to calculate the temperature. Thermocouples come in multiple types and sizes, are inexpensive to build and are highly versatile. They can also measure a wide range of temperatures, making them well suited for a variety of applications, including scientific research, industrial settings, home appliances and other environments.
Arduino and Raspberry Pi are electronic prototyping platforms used extensively in IoT devices. Table 1 describes some of the differences between the two platforms.
General-purpose I/O (GPIO) is a standard interface that Raspberry Pi and other microcontrollers use to connect to external electronic components. Recent Raspberry Pi models are configured with 40 GPIO pins, which are used for multiple purposes. For example, GPIO pins supply 3.3 volt or 5 volt direct current power, provide a ground for devices, serve as a serial peripheral interface bus, act as a universal asynchronous receiver/transmitter or deliver other functionality. One of the biggest advantages of Raspberry Pi GPIO pins is that IoT developers can control them through software, making them especially flexible and able to serve specific IoT purposes.
An IoT gateway is a physical device or software program that facilitates communications between IoT devices and the network that carries device data to a centralized platform, such as the public cloud, where data is processed and stored. Smart device gateways and cloud endpoint protection products can move data in both directions, while helping to protect data from being compromised, often employing such techniques as tamper detection, encryption, crypto engines or hardware random number generators. Gateways might also include features that enhance IoT communications, such as caching, buffering, filtering, data cleansing or even data aggregation.
The Open Systems Interconnection (OSI) model provides a foundation for internet communication, including IoT systems. The OSI model defines a standard for how devices transfer data and communicate with each other over a network and is divided into seven layers that build on top of each other:
The following list includes many of the protocols being used for IoT:
Cellular IoT protocols, such as LTE-M, narrowband IoT and 5G can also facilitate IoT communications. In fact, 5G promises to play a significant role in the coming onslaught of IoT devices.
Bluetooth, sometimes referred to as Bluetooth Classic, is typically used for different purposes than Bluetooth Low Energy. Bluetooth Classic can handle much more data but consumes a lot more power. Bluetooth LE requires less power but can’t exchange nearly as much data. Table 2 provides an overview of some of the specific differences between the two technologies.
Internet Protocol Version 6, commonly referred to as IPv6, is an upgrade from IPv4. One of the most significant changes is IPv6 increases the size of IP addresses from 32 bits to 128 bits. Because of its 32-bit limitation, IPv4 can support only about 4.2 billion addresses, which has already proved insufficient. The mounting number of IoT devices and other platforms that use IP addresses requires a system that can handle future addressing needs. The industry designed IPv6 to accommodate trillions of devices, making it well suited for IoT. IPv6 also promises improvements in security and connectivity. It’s the additional IP addresses that take center stage, however, which is why many believe that IPv6 will play a pivotal role in the future success of IoT.
The Zigbee Alliance is a group of organizations working together to create, evolve and promote open standards for IoT platforms and devices. It’s developing global standards for wireless device-to-device IoT communication and certifies products to help ensure interoperability. One of its most well-known efforts is Zigbee, an open standard for implementing low-power, self-organizing mesh networks. Zigbee-certified products can use the same IoT language to connect and communicate with each other, reducing interoperability issues. Zigbee is based on the IEEE 802.15 specification but adds network and security layers in addition to an application framework.
The following use cases represent ways IoT data analytics can benefit organizations:
Edge computing can benefit IoT in a number of ways, including the following:
The coming wave of 5G networks could impact IoT in a variety of ways:
Security remains a huge part of IoT. The Open Web Application Security Project has identified the top 10 IoT security vulnerabilities, which include the following:
An organization can take several steps to protect its IoT systems, including the following:
Organizations that want to implement an effective IoT system face a variety of challenges, including the following:
Industrial internet of things (IIoT) is often defined as a subset of IoT that focuses specifically on industrial settings, such as manufacturing, agriculture or oil and gas. However, some people in the industry define IoT and IIoT as two separate efforts, with IoT focused on the consumer side of device connectivity. In either case, IIoT falls squarely on the industrial side of the equation and is concerned primarily with the use of smart sensors and actuators to enhance and automate industrial operations.
Also known as Industry 4.0, IIoT uses smart machines that support machine-to-machine (M2M) technologies or cognitive computing technologies, such as AI, machine learning or deep learning. Some machines even incorporate both types of technologies. Smart machines capture and analyze data in real time and communicate information that can be used to drive business decisions. When compared to IoT in general, IIoT tends to have stricter requirements in such areas as compatibility, security, resilience and precision. Ultimately, IIoT aims to streamline operations, improve workflows, increase productivity and maximize automation.
The terms IoT and M2M are sometimes used interchangeably, but they aren’t the same. M2M enables networked devices to interact with each other and carry out operations without human interaction. For example, M2M is often used to enable ATMs to communicate with a central platform. M2M devices use point-to-point communication mechanisms to exchange information using a wired or wireless network. An M2M system typically relies on standard network technologies, such as Ethernet or Wi-Fi, making it cost-effective for establishing M2M communication.
IoT is often considered an evolution of M2M that increases connectivity capabilities to create a much larger network of communicating devices, relying on IP-based technologies to facilitate that communication. Standard M2M systems have limited scalability options and tend to be isolated systems that are best suited for simple device-to-device communication, typically with one machine at a time. IoT has a much broader range that can integrate multiple device architectures into a single ecosystem, with support for simultaneous communications across devices. However, IoT and M2M are similar in that both systems provide a structure for exchanging data between devices without human intervention.
The internet of everything (IoE) is a conceptual leap that reaches beyond IoT — which focuses on things — into an expanded realm of connectivity that incorporates people, process and data, along with things. The concept of IoE originated with Cisco, which stated that the “benefit of IoE is derived from the compound impact of connecting people, process, data and things, and the value this increased connectedness creates as ‘everything’ comes online.”
By comparison, IoT refers only to the networked connection of physical objects, while IoE expands this network to include people-to-people and people-to-machine connections. Cisco and other proponents believe that those who harness IoE will be able to capture new value by “connecting the unconnected.”
Enterprises implementing an IoT system should conduct a variety of testing, including the following types:
IoT asset tracking refers to the process of using IoT to monitor the location of an organization’s physical assets, no matter where they’re located or how they’re being used. Assets can include anything from delivery vans to medical equipment to construction tools. Rather than try to track these assets manually, a company can use IoT asset tracking to automatically identify the location and movement of each tracked device, helping save time and ensure greater accuracy. At the same time, organizations can use asset tracking to simplify inventory maintenance, improve asset use, and optimize workflows and daily operations.
Thingful is an IoT search engine that provides a geographical index of real-time data from connected devices around the world, using data from millions of existing public IoT data resources. The devices that generate the data can span a variety of use cases, such as energy, weather, aviation, shipping, air quality or animal tracking. The search engine enables users to find devices, data sets and real-time data sources through geolocation and presents them using a proprietary IoT device search ranking methodology. With Thingful, users can interoperate with millions of connected objects and sensors across the planet that generate real-time open data.
IoT managers can use Thingful to analyze trends, discover patterns and identify anomalies, as well as solve problems using existing data. The search engine can also help them kick-start IoT innovation in a community and help residents of that community learn about the IoT data and environment around them. Thingful is well suited to community engagement initiatives built around data and data education. Users can create accounts, set up time-series experiments, and generate statistical and analytical visualizations. They can also integrate local IoT data repositories.
Robert Sheldon is a technical consultant and freelance technology writer. He has written numerous books, articles and training materials related to Windows, databases, business intelligence and other areas of technology.
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