We live in an age when air conditioners can be operated from outside the home, watches can record heart rates, and the current locations of buses can appear in apps—the age when “things” connect to the Internet. The enormous amount of data produced by connected things has become a new resource that drives society. In this lecture, you will learn how IoT works and the characteristics and uses of big data.
What Is IoT? — The Internet of Things
IoT (Internet of Things) is a system in which not only computers but also all kinds of “things,” such as home appliances, automobiles, factory machines, and streetlights, connect to the Internet and exchange information. IoT systems basically consist of the following elements. ①Sensors: Components that measure physical quantities such as temperature, acceleration, location (GPS), illuminance, and heart rate and convert them into electrical signals (data). ②Networks: Send the measured data to servers through the Internet. ③Cloud (servers): Store and analyze the collected data. ④Actuators: Components that affect the real world by operating motors, switches, and other devices based on the analysis results. In other words, IoT is a technology that creates a cycle of “measuring the real world (sensors), collecting and analyzing data over networks, and returning the results to the real world (actuators).”
Big Data and the Three Vs
The enormous groups of data continuously generated by IoT devices, social media, e-commerce sites, transportation IC cards, and other sources are called big data. Its characteristics are organized into the 3 Vs. ①Volume: The data is so enormous that conventional databases cannot handle it all. ②Variety: Data comes in many forms, including not only tables of numerical values but also text, images, audio, video, and location information. In particular, data that has not been organized into tables is called unstructured data, and it makes up a large portion of big data. ③Velocity: Data is generated and updated extremely quickly, so real-time processing is required. In recent years, Veracity (accuracy) and Value have sometimes been added, resulting in the terms 4 Vs and 5 Vs.
Uses of Big Data and a Data-Driven Society
Big data creates value only after it has been analyzed. An e-commerce site’s “recommendations for you” are based on analysis of purchase history (recommendation systems); a car navigation system’s traffic forecasts are based on vehicle travel data; and convenience-store product selection is based on combining sales data (POS data) with weather data. Big data is also used to predict the spread of infectious diseases and for disaster prevention. A society in which decisions are made based on the results of data analysis rather than intuition or experience is called a data-driven society. Machine learning (the previous lesson) uses big data as “learning material,” so IoT, big data, and AI are developing as a set of three technologies that strengthen one another.
Challenges — Privacy and Security
Convenience also brings challenges. The first is privacy. When location information and purchase history are combined, an individual’s behavior can become clear in detail. Therefore, the Act on the Protection of Personal Information establishes rules such as using data as anonymously processed information that has been modified so that specific individuals cannot be identified. The second is security. As more things connect to the Internet, the number of possible entry points for attacks also increases. There have been actual cases in which IoT devices using their default passwords were taken over by malware and made to participate in attacks all at once (the Mirai botnet). The third challenge is the concentration of wealth and power in large companies that possess data. It is important to consider both the perspective of those who “use” data and that of those who “provide” it.
- IoT = the Internet of Things. A cycle of sensors (measure) → networks (send) → cloud (analyze) → actuators (operate).
- The 3 Vs of big data = Volume · Variety · Velocity.
- Unstructured data (data such as text, images, and video that is not in table form) makes up a large portion of big data.
- A data-driven society = a society that makes decisions based on data analysis rather than intuition or experience.
- IoT, big data, and AI strengthen one another (data becomes learning material).
- Challenges include privacy (rules such as anonymously processed information) and the security of IoT devices.
Practice Questions
- Explain the difference between the roles of a “sensor” and an “actuator” in an IoT system.
- List all three Vs that describe the characteristics of big data and briefly explain each one.
- Using smart agriculture as an example, explain how the basic IoT structure (measure → send → analyze → operate) is implemented.
- Give one challenge associated with the spread of IoT and big data from each of the perspectives of privacy and security.
Answers and Explanations
- Answer: A sensor measures physical quantities in the real world, such as temperature, location, and heart rate, and converts them into data (electrical signals). It has the role of “input.” An actuator operates motors, switches, and other devices based on the results of analysis and decisions, affecting the real world. It has the role of “output.”
Explanation: Remember the contrast in direction: “real world → data” is a sensor, while “data → real world” is an actuator. - Answer: Volume = Data is so enormous that conventional systems cannot handle it all. Variety = Data comes in many forms, including not only numerical values but also text, images, audio, video, and location information. Velocity = Data is generated and updated quickly, so processing close to real time is required.
Explanation: Learn the English and Japanese terms for the 3 Vs together. You may receive extra credit if you mention that adding Veracity and Value expands the concept to the 4 Vs and 5 Vs. - Answer: Sensors installed in a field measure soil moisture and air temperature (measure), and the data is sent to the cloud through a network (send). Analysis of the stored data determines whether there is insufficient moisture or another condition (analyze), and an irrigation device (actuator) automatically operates based on the result (operate).
Explanation: The answer is correct if the four stages are matched in order. Other examples, such as predictive maintenance in factories or smart homes, are also acceptable if the structure is correct. - Answer: Privacy: When data such as location information and purchase history is combined, an individual’s behavior may be identified in detail, so appropriate protection, such as anonymous processing, is necessary. Security: As more devices connect to the Internet, there are more entry points for attacks, and cases have occurred in which IoT devices left with their default passwords were taken over by malware and misused in attacks.
Explanation: The key points are whether you explain the structure of privacy as “identification through combination” and security as “connected things = an increase in attack targets.”