This page has only limited features, please log in for full access.
The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must be environmentally-friendly, hence require a move towards green IoT. Green IoT leads to an eco-friendly environment, which is more sustainable for smart cities. Therefore, it is essential to address the techniques and strategies for reducing pollution hazards, traffic waste, resource usage, energy consumption, providing public safety, life quality, and sustaining the environment and cost management. This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly. Furthermore, the survey focuses on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities. Finally, we discuss challenges and opportunities for future research in smart city applications.
Faris. A. Almalki; S. H. Alsamhi; Radhya Sahal; Jahan Hassan; Ammar Hawbani; N. S. Rajput; Abdu Saif; Jeff Morgan; John Breslin. Green IoT for Eco-Friendly and Sustainable Smart Cities: Future Directions and Opportunities. Mobile Networks and Applications 2021, 1 -25.
AMA StyleFaris. A. Almalki, S. H. Alsamhi, Radhya Sahal, Jahan Hassan, Ammar Hawbani, N. S. Rajput, Abdu Saif, Jeff Morgan, John Breslin. Green IoT for Eco-Friendly and Sustainable Smart Cities: Future Directions and Opportunities. Mobile Networks and Applications. 2021; ():1-25.
Chicago/Turabian StyleFaris. A. Almalki; S. H. Alsamhi; Radhya Sahal; Jahan Hassan; Ammar Hawbani; N. S. Rajput; Abdu Saif; Jeff Morgan; John Breslin. 2021. "Green IoT for Eco-Friendly and Sustainable Smart Cities: Future Directions and Opportunities." Mobile Networks and Applications , no. : 1-25.
A recent market prediction is that 5G Fixed Wireless Access (FWA) will more than double over the next five years and trials at the same period in London suggest promising results. However, the shift to 5G FWA has raised a new set of research challenges in relation to speed of deployment and re-deployment, coverage, power consumption, end user mobility and last mile connectivity, to name just a few, because of the much higher expectations. A recent review reveals that key 5G Physical Layer technologies that will enable wide mobile and FWA have not kept up pace. In response to some of those research challenges, this paper presents the design of a 5G Multiple Input Multiple Output (MIMO) Antenna that is mounted on a tethered aerostat, and the combination of which serves as a 5G FWA aerial station. The antenna design features several novelties and the aerial station can provide last mile connectivity to a wide coverage footprint, with moderate power consumption and operating at high speeds. Both the evaluation of the antenna performance using several key performance indicators and the validation of the aerial station as a 5G FWA in a wireless sensor network (WSN) proof-of-concept application reveal efficiency gains.
Faris A. Almalki; Marios C. Angelides. An enhanced design of a 5G MIMO antenna for fixed wireless aerial access. Cluster Computing 2021, 1 -16.
AMA StyleFaris A. Almalki, Marios C. Angelides. An enhanced design of a 5G MIMO antenna for fixed wireless aerial access. Cluster Computing. 2021; ():1-16.
Chicago/Turabian StyleFaris A. Almalki; Marios C. Angelides. 2021. "An enhanced design of a 5G MIMO antenna for fixed wireless aerial access." Cluster Computing , no. : 1-16.
When integrating the Internet of Things (IoT) with Unmanned Aerial Vehicles (UAVs) occurred, tens of applications including smart agriculture have emerged to offer innovative solutions to modernize the farming sector. This paper aims to present a low-cost platform for comprehensive environmental parameter monitoring using flying IoT. This platform is deployed and tested in a real scenario on a farm in Medenine, Tunisia, in the period of March 2020 to March 2021. The experimental work fulfills the requirements of automated and real-time monitoring of the environmental parameters using both under- and aboveground sensors. These IoT sensors are on a farm collecting vast amounts of environmental data, where it is sent to ground gateways every 1 h, after which the obtained data is collected and transmitted by a drone to the cloud for storage and analysis every 12 h. This low-cost platform can help farmers, governmental, or manufacturers to predict environmental data over the geographically large farm field, which leads to enhancement in crop productivity and farm management in a cost-effective, and timely manner. Obtained experimental results infer that automated and human-made sets of actions can be applied and/or suggested, due to the innovative integration between IoT sensors with the drone. These smart actions help in precision agriculture, which, in turn, intensely boost crop productivity, saving natural resources.
Faris Almalki; Ben Soufiene; Saeed Alsamhi; Hedi Sakli. A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs. Sustainability 2021, 13, 5908 .
AMA StyleFaris Almalki, Ben Soufiene, Saeed Alsamhi, Hedi Sakli. A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs. Sustainability. 2021; 13 (11):5908.
Chicago/Turabian StyleFaris Almalki; Ben Soufiene; Saeed Alsamhi; Hedi Sakli. 2021. "A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs." Sustainability 13, no. 11: 5908.
Healthcare is one of the most promising domains for the application of Internet of Things- (IoT-) based technologies, where patients can use wearable or implanted medical sensors to measure medical parameters anywhere and anytime. The information collected by IoT devices can then be sent to the health care professionals, and physicians allow having a real-time access to patients’ data. However, besides limited batteries lifetime and computational power, there is spatio-temporal correlation, where unnecessary transmission of these redundant data has a significant impact on reducing energy consumption and reducing battery lifetime. Thus, this paper aims to propose a routing protocol to enhance energy-efficiency, which in turn prolongs the sensor lifetime. The proposed work is based on Energy Efficient Routing Protocol using Dual Prediction Model (EERP-DPM) for Healthcare using IoT, where Dual-Prediction Mechanism is used to reduce data transmission between sensor nodes and medical server if predictions match the readings or if the data are considered critical if it goes beyond the upper/lower limits of defined thresholds. The proposed system was developed and tested using MATLAB software and a hardware platform called “MySignals HW V2.” Both simulation and experimental results confirm that the proposed EERP-DPM protocol has been observed to be extremely successful compared to other existing routing protocols not only in terms of energy consumption and network lifetime but also in terms of guaranteeing reliability, throughput, and end-to-end delay.
Faris A. Almalki; Soufiene Ben Othman; Fahad A. Almalki; Hedi Sakli. EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT. Journal of Healthcare Engineering 2021, 2021, 1 -15.
AMA StyleFaris A. Almalki, Soufiene Ben Othman, Fahad A. Almalki, Hedi Sakli. EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT. Journal of Healthcare Engineering. 2021; 2021 ():1-15.
Chicago/Turabian StyleFaris A. Almalki; Soufiene Ben Othman; Fahad A. Almalki; Hedi Sakli. 2021. "EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT." Journal of Healthcare Engineering 2021, no. : 1-15.
Nowadays, IoT technology is used in various application domains, including the healthcare, where sensors and IoT enabled medical devices exchange data without human interaction to securely transmit collected sensitive healthcare data towards healthcare professionals to be reviewed and take proper actions if needed. The IoT devices are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. In healthcare applications, many miniaturized devices are exploited for healthcare data collection and transmission. Thus, there is a need for secure data aggregation while preserving the data integrity and privacy of the patient. For that, the security, privacy, and aggregation of health data are very important aspects to be considered. This paper proposes a novel secure data aggregation scheme called “An Efficient and Privacy-Preserving Data Aggregation Scheme with authentication for IoT-Based Healthcare applications” (EPPDA). EPPDA is based to verification and authorization phase to verify the legitimacy of the nodes that need to join the process of aggregation. EPPDA, also, uses additive homomorphic encryption to protect data privacy and combines it with homomorphic MAC to check the data integrity. The major advantage of homomorphic encryption is allowing complex mathematical operations to be performed on encrypted data without knowing the contents of the original plain data. The proposed system is developed using MySignals HW V2 platform. Security analysis and experimental results show that our proposed scheme guarantees data privacy, messages authenticity, and integrity, with lightweight communication overhead and computation.
Faris A. Almalki; Ben Othman Soufiene. EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare Applications. Wireless Communications and Mobile Computing 2021, 2021, 1 -18.
AMA StyleFaris A. Almalki, Ben Othman Soufiene. EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare Applications. Wireless Communications and Mobile Computing. 2021; 2021 ():1-18.
Chicago/Turabian StyleFaris A. Almalki; Ben Othman Soufiene. 2021. "EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare Applications." Wireless Communications and Mobile Computing 2021, no. : 1-18.
Having reliable telecommunication systems in the immediate aftermath of a catastrophic event makes a huge difference in the combined effort by local authorities, local fire and police departments, and rescue teams to save lives. This paper proposes a physical model that links base stations that are still operational with aerial platforms and then uses a machine learning framework to evolve ground-to-air propagation model for such an ad hoc network. Such a physical model is quick and easy to deploy and the underlying air-to-ground (ATG) propagation models are both resilient and scalable and may use a wide range of link budget, grade of service (GoS), and quality of service (QoS) parameters to optimise their performance and in turn the effectiveness of the physical model. The prediction results of a simulated deployment of such a physical model and the evolved propagation model in an ad hoc network offers much promise in restoring communication links during emergency relief operations.
Faris A. Almalki; Marios C. Angelides. Deployment of an aerial platform system for rapid restoration of communications links after a disaster: a machine learning approach. Computing 2019, 102, 829 -864.
AMA StyleFaris A. Almalki, Marios C. Angelides. Deployment of an aerial platform system for rapid restoration of communications links after a disaster: a machine learning approach. Computing. 2019; 102 (4):829-864.
Chicago/Turabian StyleFaris A. Almalki; Marios C. Angelides. 2019. "Deployment of an aerial platform system for rapid restoration of communications links after a disaster: a machine learning approach." Computing 102, no. 4: 829-864.