بررسی سیستماتیک کلان داده و داده کاوی در اینترنت اشیا Systematic survey of big data and data mining in internet of things

Introduction In recent years, the Internet of Things (IoT) has grown rapidly, as such, it can identify, control, and monitor each object on earth (usually called things) via the internet [1, 2, 3, 4, 5]. Kevin Ashton invented the concept of IoT in 1999 when the wider device-to-device communicational view has occurred. In the reference [5], the IoT is defined as self-organizing systems of unrestricted devices which provide converged systems that improve the efficiency of processes; it also creates a reference that can identify the objects connected to the Internet. Furthermore, it allows the establishment of types of communication and sharing of data by using IT and provides a variety of services through the interconnection of virtual and physical things based on the interoperability of information and communication technologies. Marjani et al. explain the concept of IoT by placing a sensor on anything that has an internet connection and intelligent layers using the computational methods as shown in Figure 1 [6]. A large number of communication devices are inside the sensor devices on the IoT. Data collection systems find the data and transfer them using embedded communication devices. The chain of devices and things are interconnected via various communication solutions such as Bluetooth, WIFI, ZigBee, and GSM. The communication devices transfer the data and receive the commands that allow integrating data from remote control devices. More than 50 billion devices including smartphones, laptops, sensors, and game consoles are forecasted to be connected to the internet via several disparate access networks, such as Radio Frequency Identification (RFID) and Wireless Sensor Networks. If we do not have any solution to this increasing volume of data over the time, gradually, this amount of data will stop us [7]. Therefore, we must think about the processes of transferring, processing, and storing data. The volume progress and data diversity and what we know as the big data nowadays are shown in Figure 2 [8].