## 2 Overview of Emerging Technologies  
In the current world, the proliferation of internet access has significantly increased to its peak, and the International Telecommunication Union (ITU) estimates that 4.9 billion people were connected to the internet in 2020 [12]. The Internet plays a crucial role to enhance the digital infrastructure for realizing digitalization, smart and real-time monitoring in every field. Governments in various developing countries are under an initiative to improve digital infrastructure to accelerate digitalization [13]. Parallel to the proliferation of Internet access, advancements in embedded systems, system on chip (SoC), and wireless communication protocols have enabled the widespread adoption of IoT devices in a variety of fields to support digitalization and real-time monitoring through the internet [14]. Currently, 10 billion IoT devices are deployed, and it is also predicted that the number of IoT devices will rise to 75 billion by 2025 [15]. The integration of sensors, communication protocols, and computing capability of SoC enabled the implementation of low-cost IoT devices in a variety of applications to collect real-time data and apply AI and ML models to it to achieve insightful information [16]. Intelligent things in smart cities can automatically, intelligently, and collaboratively enhance life quality, the standard of living and act as a sustainable resource ecosystem. To achieve this, advanced collaborative technologies such as IoT, AI, drones, and robotics are required to intensify the smartness of smart cities by enhancing energy efficiency, connectivity, and quality of service (QoS) [17]. Figure 3 illustrates the framework of implementing technologies such as IoT, AI, ML, edge computing, robotics, drones, and cloud collaboratively for an intelligent ecosystem. IoT refers to the billions of physical devices around the world that are now connected to the internet, all collecting and sharing data [18]. The sensing layer (perception layer), gateway layer (transport layer) and cloud layer (application layer) are the basic three components of IoT [19]. The sensing layer is the layer where the real-time sensor data of the physical things are obtained. With the communication protocol, the data is processed locally at the edge layer and sends the results to the gateway layer through the communication protocol. The gateway layer supports multiple communication protocols, and the received results from the edge layer are logged on the cloud server through internet connectivity in internet protocol (IP) [20]. AI is an area of computer science that specializes in developing and managing technology that can train to make decisions and take acts on behalf of humankind [21; 22; 23]. As discussed earlier, the number of active IoT devices is 10 billion and the amount of data from those IoT devices is large. The IoT devices are made more intelligent by the assistance of AI, especially ML which can be utilized to identify the different patterns in the data [24]. Data analysis using ML automates the creation of analytical models and it is a subset of artificial intelligence predicated on the premise that machines can learn from data, recognize patterns, and make decisions with little or no human intervention [25]. Edge computing is the processing of sensor data away from centralized nodes and near to the network's logical edge, toward individual data sources [26]. ML and DL models are currently being created and deployed using edge computing powered hardware to train on real-time data and make decisions at the edge device itself [27]. Drones are autonomous robots that fly in the sky and are associated with different applications such as disaster mitigation, communication, surveillance, transportation,  
Figure 3: Hybrid framework with the integration of multiple emerging technologies. safety and security, environmental protection, and intelligence gathering [28].