Networking Architectures and Protocols for IoT Applications in Smart Cities: Recent Developments and Perspectives

Abstract

Numerous municipalities employ the smart city model in large cities to improve the quality of life of their residents, utilize local resources efficiently, and save operating expenses. This model incorporates many heterogeneous technologies such as Cyber-Physical Systems (CPS), Wireless Sensor Networks (WSNs), and Cloud Computing (ClCom). However, effective networking and communication protocols are required to provide the essential harmonization and control of the many system mechanisms to achieve these crucial goals. The networking requirements and characteristics of smart city applications (SCAs) are identified in this study, as well as the networking protocols that can be utilized to serve the diverse data traffic flows that are required between the dissimilar mechanisms. Additionally, we show examples of the networking designs of a few smart city systems, such as smart transport, smart building, smart home, smart grid, smart water, pipeline monitoring, and control systems.

Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols

“…LoRa has a lower reach, and it can take up to three base stations to cover the entire city. The spreading factor, which determines how far and robustly the signal can travel, can increase LoRa’s transmission range [ 6 ]. However, it also increases the power consumption.…”

“…IoT will mostly be used in smart parking and vehicle-to-vehicle communication, augmented maps, data collection, smart water supply, and smart appliances at homes and offices. Smart power grids, agriculture, and health sectors are also going to be reliant on the interconnectivity of IoT devices [ 6 ]. The deployment of IoT devices has some requirements that differ from conventional wireless telecommunication requirements.…”

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

“…With latency reduced to microseconds or even nanoseconds, users can experience seamless interactions with remote systems and devices [ 68 ]. Massive capacity: 6G networks are expected to support a massive increase in connected devices and simultaneous connections, facilitating the proliferation of IoT devices, wearable technologies, and smart sensors [ 69 ]. This would enable seamless connectivity and data exchange in densely populated areas or scenarios with a high density of connected devices.…”

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies

“…Hence, overlooking this bias usually makes the ML model operate in a suboptimal way, thereby reducing the reliability of related diagnostic decisions, and making ML non-applicable in real-world clinical environments. To tackle the problems posed by cross-domain/multi-site bias, it is required to offer a concerted effort to make use of recent advances in AIoT techniques, such as fog computing, which enables distributed processing of medical imaging data at the network edge [ 11 ].…”

“…As an essential part of the AIoT system, Fog computing has been used in the design of smart cities’ services to address the scalability and latency concerns by bringing the computing resources closer to edge devices. With this computing paradigm, fog computing allows for localized processing, alleviates the need for distant data transmission, and minimizes the overall system latency, which significantly accelerates the data analysis, and cooperative decision-making in a broad range of smart city applications, such as traffic management, environmental monitoring, and public safety [ 11 ]. Moreover, the utilization of this technology serves to bolster data security and privacy measures by confining important information to the confines of the local network.…”