With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

반도체 공정 overview

Emerging technologies such as Internet of Things (IoT) can provide significant potential in Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time environmental data. IoT devices such as Unmanned Aerial Vehicles (UAVs) can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. However, the actual proliferation and exploitation of UAVs in Smart Farming has not been as robust as expected mainly due to the challenges confronted when selecting and deploying the relevant technologies, including the data acquisition and image processing methods. The main problem is that still there is no standardized workflow for the use of UAVs in such applications, as it is a relatively new area. In this article, we review the most recent applications of UAVs for Precision Agriculture. We discuss the most common applications, the types of UAVs exploited and then we focus on the data acquisition methods and technologies, appointing the benefits and drawbacks of each one. We also point out the most popular processing methods of aerial imagery and discuss the outcomes of each method and the potential applications of each one in the farming operations.

https://www.mdpi.com/2078-2489/10/11/349/pdf

A Review on UAV-Based Applications for Precision Agriculture

This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

The Internet of Things (IoT) is the next technological leap that will introduce significant improvements to various aspects of the human environment, such as health, commerce, and transport. However, despite the fact that it may bring beneficial economic and social changes, the security and the privacy protection of objects and users remain a crucial challenge that has to be addressed. Specifically, now the security measures have to monitor and control the actions both of users and objects. However, the interconnected and independent nature of objects, as well as their constrained capabilities regarding the computing resources make impossible the applicability of the conventional security mechanisms. Moreover, the heterogeneity of various technologies which the IoT combines increases the complexity of the security processes, since each technology is characterized by different vulnerabilities. Furthermore, the tremendous amounts of data which is generated by the multiple interactions between the users and objects or among the objects make harder their management and the functionality of the access control systems. In this context, this paper intends to provide a comprehensive security analysis of the IoT, by examining and assessing the potential threats and countermeasures. More detailed, after studying and determining the security requirements in the context of the IoT, we implement a qualitative and quantitative risk analysis, investigating the security threats per layer. Subsequently, based on this process we identify the suitable countermeasures and their limitations, paying special attention to the IoT protocols. Finally, we provide research directions for future work.

Securing the Internet of Things: Challenges, threats and solutions

The Internet of Things (IoT) is a megatrend that cuts across all scientific and engineering disciplines and establishes an integrating technical evolution to improve production efficiencies and daily human life. Linked machines and sensors use decision-making routines to work toward a common product or solution. Expanding this technical revolution into the value chain of complex areas such as agriculture, food production, and healthcare requires the implementation and connection of sophisticated (bio)analytical methods. Today, wearable sensors, monitors, and point-of-care diagnostic tests are part of our daily lives and improve patients' medical progression or athletes' monitoring capabilities that are already beyond imagination. Also, early contributions toward sensor networks and finally the IT revolution with wireless data collection and transmission via Bluetooth or smartphones have set the foundation to connect remote sensors and distributed analytical chemical services with centralized laboratories, cloud storage, and cloud computing. Here, we critically review those biosensor and chemosensor technologies and concepts used in an IoT setting or considered IoT-ready that were published in the period 2013-2018, while also pointing to those foundational concepts and ideas that arose over the last two decades. We focus on these sensors due to their unique ability to be remotely stationed and that easily function in networks and have made the greatest progress toward IoT integration. Finally, we highlight requirements and existing and future challenges and provide possible solutions important toward the vision of a seamless integration into a global analytical concept, which includes many more analytical techniques than sensors and includes foremost next-generation sequencing and separation principles coupled with MS detection.

A Megatrend Challenging Analytical Chemistry: Biosensor and Chemosensor Concepts Ready for the Internet of Things.

Internet of Things (IoT) constitutes the next step in the field of technology, bringing enormous changes in industry, medicine, environmental care, and urban development. Various challenges are to be met in forming this vision, such as technology interoperability issues, security and data confidentiality requirements, and, last but not least, the development of energy efficient management systems. In this paper, we explore existing networking communication technologies for the IoT, with emphasis on encapsulation and routing protocols. The relation between the IoT network protocols and the emerging IoT applications is also examined. A thorough layer-based protocol taxonomy is provided, while how the network protocols fit and operate for addressing the recent IoT requirements and applications is also illustrated. What is the most special feature of this paper, compared to other survey and tutorial works, is the thorough presentation of the inner schemes and mechanisms of the network protocols subject to IPv6. Compatibility, interoperability, and configuration issues of the existing and the emerging protocols and schemes are discussed based on the recent advanced of IPv6. Moreover, open networking challenges such as security, scalability, mobility, and energy management are presented in relation to their corresponding features. Lastly, the trends of the networking mechanisms in the IoT domain are discussed in detail, highlighting future challenges.

/pdf/network-protocols-schemes-and-mechanisms-for-internet-of-4bsu7d7ieu.pdf

Network Protocols, Schemes, and Mechanisms for Internet of Things (IoT): Features, Open Challenges, and Trends

Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the seven layers of the architecture model that are the Sensor Layer, the Link Layer, the Encapsulation Layer, the Middleware Layer, the Configuration Layer, the Management Layer and the Application Layer. Furthermore, the proposed Reference Architecture model is exemplified in a real-world application for surveying Saffron agriculture in Kozani, Greece.

Precision Agriculture: A Remote Sensing Monitoring System Architecture

Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the four layers of the architecture model that are the Sensor Layer, the Network Layer, the Service Layer and the Application Layer. A discussion is also conducted upon the challenges that smart farming monitoring systems face.

An Architecture model for Smart Farming

Emerging technologies such as Internet of Things (IoT) can provide significant potential in Precision Agriculture enabling the acquisition of real-time environmental data. IoT devices like Unmanned Aerial Vehicles (UAVs) equipped with cameras, sensors, and GPS receivers can deliver a variety of IoT services and applications related to fields management, by capturing images from great heights. However, there are many issues to be resolved before the effective use of UAVs in the agriculture domain, including the data collection and processing methods. There is still no standardized workflow and processes for most UAV-based applications for Precision Agriculture. In this paper, we summarize the data acquisition methods and technologies to acquire images in UAV-based Precision Agriculture and appoint the benefits and drawbacks of each one. We also review popular data analysis methods of remotely sensed imagery and discuss the outcomes of each method and its potential application in the farming operations.

Anna Triantafyllou

Papers

Network Protocols, Schemes, and Mechanisms for Internet of Things (IoT): Features, Open Challenges, and Trends

Precision Agriculture: A Remote Sensing Monitoring System Architecture

An Architecture model for Smart Farming

Data Acquisition and Analysis Methods in UAV- based Applications for Precision Agriculture

Leveraging fairness in LoRaWAN: A novel scheduling scheme for collision avoidance