# Data Mining Algorithms for Smart Cities: A Bibliometric Analysis
## 2 Conceptual Framework
### The Internet of Things (IoT)  
The Internet changed the way we carry out many of our daily activities, which assisted with efficiently using our significant resources and thereby improving our quality of life [20]. The IoT came to transform physical objects into smart devices that can connect and communicate over the Internet [21]. [PERSON] et al. [22] defines IoT as \"an infrastructure which can interconnect animate and inanimate objects, and communicate with them, connecting to the Internet, store data by collecting them through sensors in cloud systems and provide real-time information to people or machines\". IoT is empowered by using a few unique advances, including sensors, wireless communication, big data technologies, distributed computing, and DM techniques [23]. The main components of IoT are: (1) hardware that consists of sensors, (2) middleware that provides communication between different components, (3) data handling, and (4) data processing and visualization [24; 25].  
A report by Cisco [26] forecasts that until 2023, more than 14.7 billion Internet connections will occur for IoT applications. According to the IoT paradigm, everything and everyone can be part of the Internet. This vision redefines the way people interact with each other and the objects they are surrounded by [27]. The recent adaptation of different wireless technologies places IoT as the next revolutionary technology by benefiting from the opportunities offered by Internet technology [28]. Just like water, electricity, gas, and roads, IoT will become a new kind of infrastructure resource [29].  
The first step toward getting to a smart city is the integration of data collection mechanisms into the system [30]. We use sensors to monitor and alert changes in environments, such as temperature, weight, pressure, light conditions, noise levels, motion, humidity, chemicals, and detect the size, position, and speed of an object [31]. Sensors are often embedded in objects, such as machines or devices [32]. All these sensors provide information that enables the detection of urban dynamic patterns [33]. Sensors can be either wired or wireless. A sensor network connects sensors with one another and transmits signals [28]. The communication between devices and the Internet can be established by technologies such as Bluetooth, ZigBee [34], Wi-Fi [35], RFID, DSL, LAN [31], LoRaWAN [36], LTE, and 5G [37]. Wireless technologies reduce installation and maintenance costs, thus playing a vital role in IoT advancement. Sensor nodes report their results to a small number of special nodes, known as data sinks [25].  
In a smart city ecosystem, hard (or dedicated) sensing is the primary sensing paradigm in many applications, as it can be tailored to precisely meet application needs. On the other hand, soft sensing includes various non-dedicated sensing paradigms, such as opportunistic, participatory (i.e., crowdsensing), and social sensing, where citizens serve as sensing nodes. Soft sensing uses smartphone connection capabilities (e.g., GSM, Bluetooth, Wi-Fi) and built-in sensors, such as GPS, camera, accelerometer, gyroscope, and microphone [18].