Browsing by Author "Pedreiras, Paulo"
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- Foreword to the Special Issue on Advanced IoT Technologies in AgriculturePublication . Gonçalves, Pedro; Pedreiras, Paulo; Monteiro, AntónioIn recent decades, the perception of the impact of humanity’s ecological footprint has changed dramatically; it is now widely recognized that natural resources are limited and sensitive, and that their indiscriminate use is unsustainable and deeply impacts the well-being of people, animals and plants [1,2,3]. The awareness that in order to reverse this problem, we must Reduce, Reuse, and Recycle, leads to the emergence of new and disruptive paradigms in most aspects of human activity, including agriculture [4,5]. In fact, agriculture has a tremendous impact on food supplies for the world, but also on the environment, and can compromise the ecological balance, thus, endangering sustainability [6]. The search for new methodologies applied to agricultural production addresses recent technologies, most of which arise from the Internet of Things (IoT), enabling a massive and unprecedented deployment of digital devices and services in a range of application domains that always increases [6,7,8]. This trend, commonly referred to as Smart Farm, Precision Livestock Farm or Farm 4.0, consists of the use of a wide range of sensors that monitor the evolution of the impacted conditions in agriculture, transmitting these data through communication systems, typically wirelessly. These data are then analyzed, often using Artificial Intelligence techniques, supporting management decisions with the goal to optimize agricultural production, including economical aspects such as productivity, quality and profitability, and sustainability [9,10]. The management of agricultural processes is based on accurate information, both on current conditions and on the forecast of future developments, and it allows for gains in the efficiency of agricultural processes, both in terms of economics and environmental impact [7]. Indeed, we intend with this Special Issue on Advanced IoT Technologies in Agriculture to present developments in research, focusing on the application of new methods to pinpoint or solve problems and constraints in agriculture and livestock production, based on IoT, making use of emerging technologies such as large data, sensor networks, image analysis, unmanned aerial vehicles (UAV), mobile applications, cloud computing, robots or artificial intelligence. Examples of the application of such technologies to irrigation, fertilization, seeding, soil management, pest and disease detection, animal feeding, breeding and welfare, impacting on farming productivity, profit and environment sustainability, are also welcome.
- Recent Advances in Smart FarmingPublication . Gonçalves, Pedro; Pedreiras, Paulo; Monteiro, AntónioThe Digital Transformation, which has the Internet of Things (IoT) as one of its pillars, is penetrating all aspects of our society with dramatic effects. In fact, buzzwords such as “Smart homes”, “Smart offices”, “Smart health” and “Smart factories”, to name just a few, have become a commonplace and reflect the profound structural changes that the Digital Transformation is having in the way citizens live their lives and how businesses and industries are organized.
- SheepIT, an E-Shepherd System for Weed Control in Vineyards: Experimental Results and Lessons LearnedPublication . Gonçalves, Pedro; Nóbrega, Luís; Monteiro, António; Pedreiras, Paulo; Rodrigues, P.; Esteves, FernandoWeed control in vineyards demands regular interventions that currently consist of the use of machinery, such as plows and brush-cutters, and the application of herbicides. These methods have several drawbacks, including cost, chemical pollution, and the emission of greenhouse gases. The use of animals to weed vineyards, usually ovines, is an ancestral, environmentally friendly, and sustainable practice that was abandoned because of the scarcity and cost of shepherds, which were essential for preventing animals from damaging the vines and grapes. The SheepIT project was developed to automate the role of human shepherds, by monitoring and conditioning the behaviour of grazing animals. Additionally, the data collected in real-time can be used for improving the efficiency of the whole process, e.g., by detecting abnormal situations such as health conditions or attacks and manage the weeding areas. This paper presents a comprehensive set of field-test results, obtained with the SheepIT infrastructure, addressing several dimensions, from the animals’ well-being and their impact on the cultures, to technical aspects, such as system autonomy. The results show that the core objectives of the project have been attained and that it is feasible to use this system, at an industrial scale, in vineyards.