The growth of the global population coupled with a decline in natural resources, farmland, and the increase in unpredictable environmental conditions leads to food security is becoming a major concern for all nations worldwide. These problems are motivators that are driving the agricultural industry to transition to smart agriculture with the application of the Internet of Things (IoT) and big data solutions to improve operational efficiency and productivity. The IoT integrates a series of existing state-of-the-art solutions and technologies, such as wireless sensor networks, cognitive radio ad hoc networks, cloud computing, big data, and end-user applications. This study presents a survey of IoT solutions and demonstrates how IoT can be integrated into the smart agriculture sector. To achieve this objective, we discuss the vision of IoT-enabled smart agriculture ecosystems by evaluating their architecture (IoT devices, communication technologies, big data storage, and processing), their applications, and research timeline. In addition, we discuss trends and opportunities of IoT applications for smart agriculture and also indicate the open issues and challenges of IoT application in smart agriculture. We hope that the findings of this study will constitute important guidelines in research and promotion of IoT solutions aiming to improve the productivity and quality of the agriculture sector as well as facilitating the transition towards a future sustainable environment with an agroecological approach.

The history of human development has proven that medical and healthcare applications for humanity always are the main driving force behind the development of science and technology. The advent of Cloud technology for the first time allows providing systems infrastructure as a service, platform as a service and software as a service. Cloud technology has dominated healthcare information systems for decades now. However, one limitation of cloud-based applications is the high service response time. In some emergency scenarios, the control and monitoring of patient status, decision-making with related resources are limited such as hospital, ambulance, doctor, medical conditions in seconds and has a direct impact on the life of patients. To solve these challenges, optimal computing technologies have been proposed such as cloud computing, edge computing, and fog computing technologies. In this article, we make a comparison between computing technologies. Then, we present a common architectural framework based on fog computing for Internet of Health Things (Fog-IoHT) applications. Besides, we also indicate possible applications and challenges in integrating fog computing into IoT Healthcare applications. The analysis results indicated that there is huge potential for IoHT applications based on fog computing. We hope, this study will be an important guide for the future development of fog-based Healthcare IoT applications.

Health is gold, and good health is a matter of survival for humanity. The development of the healthcare industry aligns with the development of humans throughout history. Nowadays, along with the strong growth of science and technology, the medical domain in general and the healthcare industry have achieved many breakthroughs, such as remote medical examination and treatment applications, pandemic prediction, and remote patient health monitoring. The advent of 5th generation communication networks in the early 2020s led to the Internet of Things concept. Moreover, the 6th generation communication networks (so-called 6G) expected to launch in 2030 will be the next revolution of the IoT era, and will include autonomous IoT systems and form a series of endogenous intelligent applications that serve humanity. One of the domains that receives the most attention is smart healthcare. In this study, we conduct a comprehensive survey of IoT-based technologies and solutions in the medical field. Then, we propose an all-in-one computing architecture for real-time IoHT applications and present possible solutions to achieving the proposed architecture. Finally, we discuss challenges, open issues, and future research directions. We hope that the results of this study will serve as essential guidelines for further research in the human healthcare domain.

Across all periods of human history, the importance attributed to health has remained a fundamental and significant facet. This statement holds greater validity within the present context. The pressing demand for healthcare solutions with real-time capabilities, affordability, and high precision is crucial in medical research and technology progress. In recent times, there has been a significant advancement in emerging technologies such as AI, IoT, blockchain, and edge computing. These breakthrough developments have led to the creation of various intelligent applications. Smart healthcare applications can be realized by combining robust AI detection and prediction capabilities with edge computing architecture, which offers low computing costs and latency. In this paper, we begin by conducting a literature review of AI-assisted EC-based smart healthcare applications from the past three years. Our goal is to identify gaps and barriers in this field. We propose a smart healthcare architecture model that integrates AI technology into the edge. Finally, we summarize the challenges and research directions associated with the proposed model.

Mobile Ad hoc Networks (MANETs) are sets of autonomous mobile devices that have capacities of self-configuring, self-setting parameters for data transmission in-network. Due to flexible and convenient connectivity, MANETs have been proposed for many applications such as medicine, military, transportation, and disaster recovery. In recent years, to leverage the flexible communication capabilities of MANETs and the unlimited power of the IoT, MANETs have been integrated into IoT networks to form MANET-IoT networks that aim to provide novel solutions with unprecedented capabilities and abilities to serve humanity. However, communication between mobile ad hoc nodes and fixed network nodes of IoT faces some challenges, especially performance issues. In this paper, we propose a gateway selection mechanism for MANET-IoT networks. By taking accounting for the distance, queue length, and responsiveness of gateways, the proposed mechanism provides load balancing both in-network and between gateways. Simulation results have demonstrated that the proposed approach improves system efficiency in terms of load balancing, delay, and packet delivery ratio compared to existing schemes.

The launch of the 5th generation mobile communication system (5G) in the first years of the 21st century realized the Internet of Things (IoT) concept. This is towards the formation of a series of smart IoT ecosystems. In these applications, smart cities have received robust attention from both the academic and industrial communities. In smart cities, sensors, IoT devices, actuators, applications, and systems, hereinafter referred to as network nodes, need real-time communications to interact and exchange information. This led to the formation of mobile ad hoc networks (so-called MANETs). However, due to the mobility nature of MANETs, network nodes are frequently disconnected. This is the main cause decline in quality of service, performance, and high energy consumption. To address this issue, we designed a QoS-aware routing framework called PRP (Performance Routing Protocol). The proposed scheme selects the candidate route with the highest achieved throughput and the adaptive delay for mobility urban-MANET scenarios. The simulation results have demonstrated that our schema improves performance significantly to 20% in high mobility and network traffic scenarios compared to traditional protocols for MANETs.