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Today, despite increased information demand from consumers and food chain players alike, Europe’s food businesses and farmers are slow at adopting digital technologies. This is due in part to the inherent complexities of relevant products and processes, and in part to the dynamically changing open network organization of the food sector with its multitude of SMEs, its cultural diversity, its differences in expectations and in the ability to serve transparency needs. The agri-food sector needs to take more advantage of the potential of digital technologies. Relevant technologies may include Internet of Things, Artificial Intelligence, Big Data technologies, remote and localized sensing. This chapter will engage the agri-food community in supporting the development of solutions to remove the barriers to adoption of digital technologies, taking a multi-actor approach across different supply chains (conventional and organic) from farm to fork.

O estudo e implementação de redes de sensores sem fios é um campo emergente da eletrônica que está muito interligado com a internet das coisas. Juntas essas duas tecnologias possibilitam a recolha e transmissão de dados em cenários ondes redes comuns não são adequadas. Entretanto, devido às limitações usuais que são impostas aos equipamentos usados, a conservação de energia se torna indispensável para a sua utilização. Por conta disso, foram criados diversos mecanismos para redução no consumo de energia, uma grande parte das quais passa pela implementação de novos protocolos MAC. Este artigo explica como podem ser feitas implementações desse tipo de protocolo em um simulador, o que permite que se avalie o seu desempenho sem os custos associados com estudos no mundo real. Para tanto, foram comparados os simuladores mais comuns usados neste campo de estudo e o OMNeT++ foi escolhido como o mais adequado. Depois disso foi feita uma demonstração prática de como implementar um protocolo MAC nesse simulador e os resultados da simulação foram analisados.

Wireless mesh networking (WMN) is a continuous growing technology that has an important role towards the vision of smart agriculture. This work presents the setup and performance assessment of a wireless mesh network testbed developed within the context of PrunusPós project to collect data such as temperature and humidity of fruit crates or containers when stored or transported in refrigerated chambers. The testbed is based on ESP8266 devices connected in a wireless mesh using the painlessMesh library. A performance evaluation study was conducted with different numbers of nodes, traffic loads, and message payload sizes under unicast and broadcast communication. The impact on network performance is evaluated in terms of delivery ratio and delivery delay. This study will guide the future development of mechanisms, schemes and protocols that provide efficient bandwidth utilization and energy-efficient computing for the PrunusPós project WMN.

Este artigo visa fazer uma contextualização do conceito de Internet das Coisas (IoT), uma nova abordagem que resulta da dinamização da multipluralidade de plataformas passíveis de interligar e com os quais é possível estabelecer comunicação em rede. Estas afetam, cada vez mais, a qualidade de vida dos seus utilizadores e acabam por ter uma repercussão quotidiana na forma como estes extraem informação no meio envolvente, muitas vezes de forma invisível. No curso deste documento, também será feita uma exposição dos dispositivos de suporte que lhe estão associados, desde os microcontroladores que os operam, até aos sensores e/ou outros dispositivos, que não são mais que ferramentas que recolhem e comunicam a informação.

This paper presents the proposal, implementation and validation of a low cost fault-tolerant functional prototype for livestock monitoring. This prototype uses IoT devices, ESP8266 and ESP32, creating a mesh network, managed by the painlessMesh library, with WiFi and LoRa technologies. It allows, for instance, the collection of vital signs from animals. In comparison with the traditional method of livestock examination, this cost-efficient approach reduces manual labor and saves working time. It also improves animal health, increases profits and decreases the environmental footprint.

Obstructive sleep apnea is a respiratory problem that has serious consequences for physical and mental health, but also in monetary terms, since traffic accidents and poor work performance, among other direct consequences, are attributed to it. It is estimated that between 9% and 38% of the world’s population has this disease. This is a multifactorial disease, therefore, there are several methods of detection and treatment; however, all of them cause discomfort to the patient, or to those around them. In this article we propose a system for the detection and control of obstructive sleep apnea that promises to overcome the drawbacks of the existing therapies, therefore, potentially making it a practical and effective solution for this disease. The proof of concept presented in this paper makes use of an electromyography sensor to collect the myoelectric signal produced by the genioglossus muscle. Surface electrodes provide the electromyography signals to an ESP32 microcontroller, which has the function of analyzing and comparing the data obtained with a predefined value of the apnea threshold. After the detection of an apnea, the circuit is able to create a stimulus signal that is applied directly to the muscle, so that airway occlusion does not occur, and the user does not wake up. The data from each use are automatically sent to a database to be viewed and analyzed at a later point.

The continuous rise in the world’s population has increased the need for food, resulting in a rise of agricultural holdings to ensure the supply of these goods directly to the populations and indirectly to all processing industries in the food business. This situation has led agriculture to reinvent itself and introduce new technics and tools to ensure tighter control of the crops and increase yields in food production. However, the lack of labor coupled with the evolution of weeds resistant to herbicides created a crisis in agricultural food production. However, with the growing evolution in electronics, automation, and robotics, new paths are emerging to solve these problems. A robotic rover was designed to optimize the tasks of weed control and collection of fallen fruits of an orchard. In weed control, a localized spraying system is proposed, therefore reducing the amount of applied herbicides. With fruit collection, it is possible to direct fallen fruits for animal feeding and possible to reduce microbial activity on the next campaign crops, therefore avoiding damage. This study proposes the simulation of this robotic rover on robotic simulation software. It also proposes the replication of a similar environment of an orchard to generate an algorithm that controls the rover on the tasks of localized spraying and fallen fruit collection. Creating and testing these algorithms by using a robotic simulator speed up and ease the evaluation of different scenarios and hypotheses, with the added benefit of being able to test two tasks simultaneously. This method also allows greater freedom and creativity because there are no concerns about hardware damage. It should also be noted that development costs are very low.

This survey presents approaches and technologies for livestock identification, vital signs monitoring and location tracking. It first introduces the related concepts. Then, provides an analysis of existing solutions and highlights their strengths and limitations. Finally, it presents key challenges in the field, and discusses recent trends that must be factored in by researchers, implementers, and manufacturers towards future developments in the area.

As redes de sensores sem fios são uma tecnologia emergente que é frequentemente utilizada para monitorizar pontos ou objectos de interesse numa área. Apesar das suas muitas aplicações, este tipo de rede é frequentemente limitado pelo facto de ser muito difícil fornecer energia aos nós continuamente, forçando a utilização de baterias, o que limita as suas operações. A densidade da rede pode também levar a outros problemas. Redes esparsas requerem transmissões mais fortes e têm pouca redundância, enquanto as redes densas aumentam as hipóteses de sobre-audição e interferência. Para resolver estes problemas, vários novos protocolos de controlo de acesso ao meio (MAC) têm sido desenvolvidos ao longo dos anos. O objectivo deste estudo é avaliar a eficácia dos protocolos T-MAC, B-MAC, e RI-MAC numa rede de densidade variável utilizada para recolher dados dentro de camiões de carga que transportam frutos perecíveis. Este trabalho faz parte do projecto PrunusPós, que visa aumentar a eficiência da cultura de pêssegos e cerejas em Portugal.

Este trabalho apresenta o desenho e implementação de um protótipo funcional para avaliar e validar a utilização de técnicas de visão computacional, na identificação de contentores de resíduos no contexto de uma cidade inteli- gente. Este protótipo recorre à utilização de uma rede neuronal convolucional YOLO e de um microcomputador Jetson Nano da Nvidia. Comparativamente ao método atual de identificação de contentores de resíduos por radiofrequência, esta abordagem é mais ágil e diminui os recursos necessários para implementa- ção, contribuindo para poupar nos gastos logísticos e de implementação da gestão inteligente de resíduos.

Weeds, pathogens, and animal pests are among the pests that pose a threat to the productivity of crops meant for human consumption. Bird-caused crop losses pose a serious and costly challenge for farmers. This work presents a survey on bird deterrent solutions for crop protection. It first introduces the related concepts. Then, it provides an extensive review and categorization of existing methods, techniques, and related studies. Further, their strengths and limitations are discussed. Based on this review, current gaps are identified, and strategies for future research are proposed.

Alavancagem da atividade económica nas pequenas e médias empresas de sectores estratégicos e tradicionais: Encorajamento na utilização de novas tecnologias, Oportunidade enorme para as novas TIC nas empresas agroalimentares, Incorporar recursos inovadores com valor acrescentado, melhorar as competências de atividade das PME, promover a modernização do sector empresarial regional, a utilização das TIC irá fomentar a economia e a competitividade dos sectores agro-alimentares tradicionais

Precision irrigation and optimization of water use have become essential factors in agricul- ture because water is critical for crop growth. The proper management of an irrigation system should enable the farmer to use water efficiently to increase productivity, reduce production costs, and maxi- mize the return on investment. Efficient water application techniques are essential prerequisites for sustainable agricultural development based on the conservation of water resources and preservation of the environment. In a previous work, an off-policy deep reinforcement learning model, Deep Q-Network, was implemented to optimize irrigation. The performance of the model was tested for tomato crop at a site in Portugal. In this paper, an on-policy model, Advantage Actor–Critic, is implemented to compare irrigation scheduling with Deep Q-Network for the same tomato crop. The results show that the on-policy model Advantage Actor–Critic reduced water consumption by 20% compared to Deep Q-Network with a slight change in the net reward. These models can be developed to be applied to other cultures with high production in Portugal, such as fruit, cereals, and wine, which also have large water requirements.