IoT in Agriculture

Dear Colleagues,

This Special Issue is dedicated to new advances in IoT agro-intelligence and related areas. The objective is to publish the work developed in applications in agriculture and the focus is on the presentation of several theoretical and practical problems, where topics of interest include, but are not limited to, the following:

• Signal processing for IoT;
• IoT sensors;
• IoT connectivity: LoRa, Sig Fox, NB-IoT, 5G communications;
• Machine learning;
• Artificial/augmented intelligence;
• Forward error correction (FEC) for IoT; IoT security

Technological developments have reached the agricultural sector to facilitate people's lives and streamline processes. Production planning and control are criteria for success and today’s agriculture is synonymous with advanced machinery and cutting edge technology all in the name of efficiency, productivity and sustainability, both financial and environmental, of the business. Precision agriculture, a system based on new technologies that controls and analyzes all production, plays an important role in this new paradigm that we call IoT agro-intelligence.

The use of advanced technologies allows tracing, monitoring, automation and data analysis operations and can be divided into three main strands. The first one concerns the integration between hardware elements, including connectivity networks for specialized automation applications (robots, drones, sensors, among others), and software, in which machine-to-machine (M2M) and IoT (Internet solutions of Things) can be applied to irrigation systems, greenhouse monitoring, livestock, soil management and scanning, e.g. a significant part of applications depends on the assembly of a reliable communication channel in heterogeneous networks comprising different communication technologies, such as the Internet. In IoT networks, we expect a reliable and satisfactorily fast communication channel that will help to reduce the power consumption demands of the deployed devices. The increasing communication complexity and more diverse communication technology base leads to serious challenges in the process of communication diagnosis and optimization of specific applications and services. Since intelligent agriculture in general requires a large number of sensors in order to obtain an effective control and thus increase productivity, the second aspect is related to the collection and storage of large volumes of data (big data) produced by systems in the field that require high storage capacity in a data center, fast access to data and attention to availability, reliability and security of information. In this field of security, there are advanced solutions that manage to protect the distributed networks of hardware and software, not allowing the intrusion of external systems, as well as data, with analytical systems and management dashboards in the data center and the Cloud, with access control and operational profiles. Finally, it is important to add the aspect related to data analytics systems in support of decision making and the construction of predictive management models, based on the Cloud as a service platform. Given the complexity and volume of data, processing requires high-performance machines, with scalability and speed in obtaining results.

Dr. Salviano Pinto Soares
Dr. Antonio Valente
Dr. Filipe Cabral Pinto
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• signal processing for IoT
• IoT sensors
• LoRaWAN
• NB-IoT systems
• cluster library
• mesh networks
• artificial/augmented intelligence in agriculture
• machine learning
• communication networks evaluation and optimization
• security