Plant leaf disease classification using EfficientNet deep learning model

Dense convolutional neural networks based multiclass plant disease detection and classification using leaf images

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic’s potential impact on the adoption of the Internet of Things (IoT) in various broad sectors, namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in the wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.

Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT.

Determining how to structure vehicular network environments can be done in various ways. Here, we highlight vehicle networks' evolution from vehicular ad-hoc networks (VANET) to the internet of vehicles (IoVs), listing their benefits and limitations. We also highlight the reasons in adopting wireless technologies, in particular, IEEE 802.11p and 5G vehicle-to-everything, as well as the use of paradigms able to store and analyze a vast amount of data to produce intelligence and their applications in vehicular environments. We also correlate the use of each of these paradigms with the desire to meet existing intelligent transportation systems' requirements. The presentation of each paradigm is given from a historical and logical standpoint. In particular, vehicular fog computing improves on the deficiences of vehicular cloud computing, so both are not exclusive from the application point of view. We also emphasize some security issues that are linked to the characteristics of these paradigms and vehicular networks, showing that they complement each other and share problems and limitations. As these networks still have many opportunities to grow in both concept and application, we finally discuss concepts and technologies that we believe are beneficial. Throughout this work, we emphasize the crucial role of these concepts for the well-being of humanity.

Computing Paradigms in Emerging Vehicular Environments: A Review

The monitoring and control of crops in precision agriculture sometimes requires a high collection frequency of information (e.g., temperature, humidity, and salinity) due to the variability in crops. Data acquisition and transmission are generally achieved thanks to wireless sensor networks. However, sensor nodes have limited resources. Thus, it is necessary to adapt the increase in sampling frequency for different crops, under application constraints (reliability, packet delay, and lifetime duration). In this paper, we propose to properly tune IEEE 802.15.4 MAC parameters ( macMinBE and macMaxCSMABackoffs ) and the sampling frequency of deployed sensor nodes. An analytical model of network performance is derived and used to perform the tuning of these tradeoff parameters. Simulation analysis shows that our scheme provides an efficient increase of sampling frequency of sensor nodes while satisfying application requirements.

Performance Management of IEEE 802.15.4 Wireless Sensor Network for Precision Agriculture

https://doi.org/10.1016/j.heliyon.2023.e15486

Towards associating negative experiences and recommendations reported by Hajj pilgrims in a mass-scale survey

Wireless sensing technology becomes a new scientific instrument for physical and environmental monitoring. The technology involves deploying a large number of tiny sensor nodes that cooperatively sense and report a specific condition at various locations to the base station. This class of applications faces many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Therefore, sensing applications require intelligent, energy-efficient and self-organizing approaches. This paper proposes a novel intelligent routing approach for wireless sensor networks (WSNs) that achieves between 25%–50% energy saving compared to the existing WSNs' routing algorithms. It also improves the overall performance of WSNs for real world applications.

Najla Al-Nabhan

Papers

Towards associating negative experiences and recommendations reported by Hajj pilgrims in a mass-scale survey

An intelligent routing approach for wireless sensor networks