IoT-Based Systems for Smart and Sustainable Agriculture

Dear Colleagues,

The last few decades have witnessed the advancement of the Internet of Things (IoT) and multiple wireless sensor networks (WSNs), in both the academic and industrial worlds. Among various scenarios in which these paradigms can find an application, a relevant area, subject to ever-increasing interest and to the participation of different actors, is represented by agriculture, which is becoming “smarter and smarter” in different ways. Indeed, farming is facing many economic challenges in terms of productivity, cost-effectiveness, and quality, as well as an increasing labor shortage partly due to depopulation of rural areas.

In this historical moment, in which the indiscriminate use of pesticides, climate change, reduction of water supplies, depletion of resources, as well as loss of soil quality, which are already limiting the amount of food produced by the world’s farmlands, it is necessary to identify the best approaches to tackle these challenges. Furthermore, reliable detection, accurate identification, and proper quantification of pathogens and other factors and diseases affecting both plant and animal health are critical and need to be kept under control in order to reduce economic expenditures, trade disruptions, and human health risks.

Agriculture needs to be enhanced by new technologies in order to make it sustainable in a smart way. In the last few years, several IoT-based products dedicated to farming have appeared, but there are still some remaining issues, ranging from data acquisition, interpretation, and reliable collection in some potentially harsh radio environments. Moreover, together with the growing involvement of various technologies in the agricultural field, another key point is represented by managing the harvested data not only in-site, at the farmer’s estate, but in a logically centralized and aggregated way, thus exploiting the characteristics of cloud/edge computing-based infrastructures and architectures. In this way, the information is available at different levels, with the aim to be processed applying different approaches (e.g., using machine learning algorithms, as well as geographically distributed technologies), in order to offer specific services. Different access and handling policies can be applied to various actors, ranging from the farmer (interested in improving its crop’s health and quality adopting some treatments based on a set of practices obtained by multiple data analyses) to the final consumer, aware of the whole traceability process for the food supply chain “from the field to the fork”.

One challenging issue of next generation agriculture is big data. A new data processing culture is required to handle and exchange the huge amount of data in a reliable, secure, and lawful way. Data reliability means that the own collected daily data and the aggregated data from a third-party data provider are reliable, verified, and accurate in time and value. Data security ensures and guaranties that data at any transfer path will never be manipulated by criminal activities to avoid wrong data supply in smart agriculture applications. This can be achieved with a good user authentication implementation and sufficient data encryption before the data leave the protected owner zone—and, finally, the lawful handling of private generated data, which must be treated as a private property of the data owner and on which it must have the opportunity to sell its own data as a product. A fair data exploitation is the most exchange-related aspect in future data-driven agriculture. This can be only achieved with the most reliable data sources possible and strong data security.

This Special Issue calls for reports on high quality, up-to-date innovative original current advances in solutions and research for smart and sustainable agriculture, ranging from IoT, WSN, efficient sensing, cloud/edge computing, smart actuators, etc.

Some topics of interest include but are not limited to:

• Data-aware networking in smart agriculture;
• Sensor network deployment for smart agriculture;
• Cloud computing for smart agriculture;
• Edge computing for smart agriculture;
• Cyberphysical systems (CPS) for smart agriculture;
• Internet of Things (IoT) for smart agriculture;
• Farm services and oriented applications for agri-food systems;
• Modeling and metrics for sensing in smart agriculture;
• Implementation and prototypes of WSN agriculture showcases;
• Data security by user authentication and data encryption;
• Security by design philosophy in agriculture;
• Cost-effective sensor development for smart agriculture.

Prof. Dr. Gianluigi Ferrari
Dr. Luca Davoli
Dr. Roberto Fresco
Dr. Baran Çürüklü
Prof. Dr. José-Fernán Martínez
DI(FH) Erwin Kristen
Guest Editors

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