Design and Development of Smart Parking System Based on Fog Computing and Internet of Things

Abstract

Current parking systems employ a single gateway-centered solution (i.e., cloud) for data processing which leads to the possibility of a single point of failure, data loss, and high delays. Moreover, the parking-spot selection process considers criteria that do not maximize parking utilization and revenue. The pricing strategy does not achieve high revenue because a fixed pricing rate is utilized. To address these issues, this paper proposes a smart parking system based on the Internet of Things (IoT) that provides useful information to drivers and parking administrators about available parking spots and related services such as parking navigation, reservation, and availability estimation. A multi-layer architecture is developed that consists of multiple sensor nodes, and fog and cloud computing layers. The acquired parking data are processed through fog computing nodes to facilitate obtaining the required real-time parking data. A novel algorithm to obtain the optimal parking spot with the minimum arrival time is also presented. Proof-of-concept implementation and simulation evaluations are conducted to validate the system performance. The findings show that the system reduces the parking arrival time by 16–46% compared to current parking systems. In addition, the revenue is increased for the parking authority by 10–15%.

Design and Implementation of Office Automation System Based on Internet of Things Technology

“…The mobile office platform is composed of two parts: Web terminal and mobile client [13,14]. The web side has the administrator authority function, which can add and delete ordinary administrators and can add and modify resources.…”

Enhancing Security Mechanisms for IoT-Fog Networks

“…3 provides a schematic depiction of our network infrastructure, showcasing the integration between IoT devices and the Fog server. In the subsequent section, we'll delve into the specific security protocol implemented for communication between the node and the IoT devices [54], [55]. Before the IoT device gains access to the essential neural network weight values, it engages in an intricate initiation sequence, as we see in Fig.…”

Guiding to available parking spots with AR device

“…In this section, some related works of smart parking are presented. The Kudai parking lot [4], which encompasses 2500 parking spaces, was selected for the simulation and implementation of the intelligent parking system. The hardware components employed in the experiment consist of ultrasonic and geomagnetic sensors, RFID (radio frequency identification devices)card reader modules, S50 RFID cards, LoRa (Long Range) radio modules, rechargeable lithium-ion batteries, photovoltaic panels, LED (light-emitting diode)lights, Raspberry Pi 3, and an HP workstation.…”