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- An Eco-Energetic Performance Comparison of Dehumidification Systems in High-Moisture Indoor EnvironmentsPublication . Santos, Alexandre Fernandes; Gaspar, Pedro Dinis; Souza, Heraldo; Caldeira, João M. L. P.; Soares, Vasco N. G. J.This study discusses the choice of dehumidification systems for high-moisture indoor environments, such as indoor swimming pools, supported by an eco-energetic performance comparison. Initially, the causes of the high relative humidity and condensation in these spaces are reported, as well as the available dehumidification technologies. Two different solutions are described: desiccant wheel dehumidification and re-cooling. The energy demand required by a refrigeration system is lower than the desiccant wheel; however, the former system requires less maintenance and does not require refrigerant fluid. An eco-energetic comparison is performed between the two systems in two countries with different energy matrices (Brazil and USA). In Brazil, the desiccant wheel is the best choice for the past 10 years, with a predicted 351,520 kgCO2 of CO2 emissions, which is 38% lower than the refrigeration system. In the USA, the best option is the refrigeration system (1,463,350 kgCO2), a 12% more efficient option than desiccant wheels. This model can be considered for energy and CO2 emissions assessment, predicting which system has better energy efficiency and lower environmental impact, depending on the refrigerant type, location and environmental conditions.
- Bird Deterrent Solutions for Crop Protection: Approaches, Challenges, and OpportunitiesPublication . Micaelo, Eduardo; Lourenço, Leonardo G. P. S; Gaspar, Pedro Dinis; Caldeira, João M. L. P.; Soares, Vasco N. G. J.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.
- Radio-Frequency Identification Traceability System Implementation in the Packaging Section of an Industrial CompanyPublication . Gomes, Hermenegildo; Navio, Francisco; Gaspar, Pedro Dinis; Soares, Vasco N. G. J.; Caldeira, João M. L. P.In recent years, radio-frequency identification (RFID) has aroused significant interest from industry and academia. This demand comes from the technology’s evolution, marked by a reduction in size, cost, and enhanced efficiency, making it increasingly accessible for diverse applications. This manuscript presents a case study of the implementation of an RFID traceability system in the packaging section of an industrial company that produces test equipment for the automotive wiring industries. The study presents the proposal and execution of a prototype asset-tracking system utilising RFID technology, designed to be adaptable and beneficial for various industrial settings. The experiments were carried out within the company’s shop-floor environment, alongside the existing barcode system, with the primary objective of evaluating and comparing the proposed solution. The test results demonstrate a significant enhancement in production efficiency, with substantial optimization achieved. The time required for asset identification and tracking was significantly reduced, resulting in an average time of approximately 43.62 s and an approximate 3.627% improvement in the time required to read the test sample of assets when compared to the barcode system. This successful implementation highlights the potential of RFID technology in improving operations, reducing working time, and enhancing traceability within industrial production processes.
- Avaliação de Desempenho de uma Rede em Malha Sem Fios para Rastreabilidade daQualidade Alimentar no Pós-colheita de Produtos Frutícolas: Um Caso de EstudoPublication . Costa, Tiago; Santos, Luís; Caldeira, João M. L. P.; Soares, Vasco N. G. J.; Gaspar, Pedro DinisEste artigo apresenta a avaliação de desempenho de uma rede de sensores sem fios organizada em malha, para monitorização da temperatura e humidade em produtos hortofrutícolas quando transportados em galeras de camiões. Para tal é proposta uma solução de software, usando a biblioteca painlessMesh para gestão da rede em malha, desenvolvida para dispositivos com módulo de comunicação ESP8266 alimentados por baterias. Esta solução tem como objetivo minimizar os gastos energéticos dos nós sensores usados. Para efeitos de validação desta proposta foi usada uma área correspondente à galera de um camião, onde foram distribuídos cinco nós sensores e um nó raiz. Os testes foram desenvolvidos considerando quatro modelos diferentes envolvendo, variações na garantia de entrega das mensagens, o número de tentativas até sucesso de entrega e duração dos tempos de adormecimento dos nós. A avaliação de desempenho da solução teve por objetivo determinar, a taxa de conectividade, a taxa de envio após conexão e as taxas de entrega das primeira e segunda tentativas. Os resultados obtidos evidenciam que a confirmação de entrega de mensagens não traz mais valias à solução, contribuindo apenas para o incremento dos gastos energéticos. O uso de tempos sincronizados no adormecimento dos nós, demonstrou também resultados piores que o uso de tempos assíncronos. Estes resultados permitem criar uma base de conhecimento para a utilização desta solução em contexto real.
- Artificial Intelligence Decision Support System Based on Artificial Neural Networks to Predict the Commercialization Time by the Evolution of Peach QualityPublication . Ananias, Estevão; Gaspar, Pedro Dinis; Soares, Vasco N. G. J.; Caldeira, João M. L. P.Climacteric fruit such as peaches are stored in cold chambers after harvest and usually are maintained there until the desired ripening is reached to direct these fruit to market. Producers, food industries and or traders have difficulties in defining the period when fruit are at the highest level of quality desired by consumers in terms of the physical‐chemical parameters (hardness –H–, soluble solids content –SSC–, and acidity –Ac–). The evolution of peach quality in terms of these parameters depends directly on storage temperature –T– and relative humidity –RH–, as well on the storage duration –t–. This paper describes an Artificial Intelligence (AI) Decision Support Sys‐ tem (DSS) designed to predict the evolution of the quality of peaches, namely the storage time re‐ quired before commercialization as well as the late commercialization time. The peaches quality is stated in terms of the values of SSC, H and Ac that consumers most like for the storage T and RH. An Artificial neuronal network (ANN) is proposed to provide this prediction. The training and val‐ idation of the ANN were conducted with experimental data acquired in three different farmers’ cold storage facilities. A user interface was developed to provide an expedited and simple predic‐ tion of the marketable time of peaches, considering the storage temperature, relative humidity, and initial physical and chemical parameters. This AI DSS may help the vegetable sector (logistics and retailers), especially smaller neighborhood grocery stores, define the marketable period of fruit. It will contribute with advantages and benefits for all parties—producers, traders, retailers, and con‐ sumers—by being able to provide fruit at the highest quality and reducing waste in the process. In this sense, the ANN DSS proposed in this study contributes to new AI‐based solutions for smart cities.
- Detecting and monitoring the development stages of wild flowers and plants using computer vision: Approaches, challenges and opportunitiesPublication . Videira, João; Gaspar, Pedro Dinis; Soares, Vasco N. G. J.; Caldeira, João M. L. P.Wild flowers and plants play an important role in protecting biodiversity and providing various ecosystem services. However, some of them are endangered or threatened and are entitled to preservation and protection. This study represents a first step to develop a computer vision system and a supporting mobile app for detecting and monitoring the development stages of wild flowers and plants, aiming to contribute to their preservation. It first introduces the related concepts. Then, surveys related work and categorizes existing solutions presenting their key features, strengths, and limitations. The most promising solutions and techniques are identified. Insights on open issues and research directions in the topic are also provided. This paper paves the way to a wider adoption of recent results in computer vision techniques in this field and for the proposal of a mobile application that uses YOLO convolutional neural networks to detect the stages of development of wild flowers and plants.