Como a função da ARENA é possibilitar o desenvolvimento de soluções, a quantidade de trabalhos possíveis a partir de sua implementação é enorme. Em relação à estrutura de experimentação a implementação de alguns recursos poderiam facilitar o desenvolvimento de sistemas mais complexos. (QI; LIU, 2018) (REINA et al., 2017.) (MILLARD et al., 2018.) (WHEELER et al., 2019), apresentaram soluções que utilizavam a AR para gerar gráficos e painéis que apresentavam diversas informações úteis (dados de sensores, variáveis de controle, etc.) para a execução dos experimentos, por isso seria extremamente valioso dotar a ARENA com funções semelhantes.
O sistema de rastreamento utiliza dados de câmeras para fornecer as posições de robôs. Portanto um armazém comum, além de possuir dimensões elevada, apresentam estruturas como prateleiras, ou até mesmo produtos, que impedem que as câmeras tenham acesso a certos pontos. Deste modo, é necessário que seja utilizada uma grande quantidade de aparelhos para cobrir toda a área do armazém. Como a carga computacional para executar as operações de rastreamento é elevada, seria inviável utilizar o servidor para executar todas essas operações. Assim, um trabalho extremamente útil para MRS, seria o desenvolvimento de um dispositivo que tivesse a capacidade de processar as imagens obtidas e alimentar o servidor com as coordenadas dos robôs em operação. Este sistema poderia ainda executar as operações de controle dos robôs, aliviando assim a carga computacional executada pelos servidores.
Em certos casos, os sistemas que dependem da análise de imagem, poderiam ser inviabilizados por questões técnicas ou operacionais, por exemplo: ambientes com condições de iluminação deficitária ou com características que inviabilizem a cobertura total por câmeras. O desenvolvimento de um sistema de rastreamento mais flexível como o RFID (Radio Frequency Identification) que utiliza ondas de rádio, poderia ser uma solução viável para atender a estas condições.
Em relação à operação específica dos armazéns inteligentes, uma série de soluções poderiam ser desenvolvidas. Sendo assim, o escalonamento e gerenciamento de tarefas com análise de prioridade, otimização de rotas, entre outros, poderiam ser fruto de diversos trabalhos
que utilizem diferentes abordagens. Algoritmos genéticos, programação linear e redes neurais são técnicas que podem ser utilizadas para implementar soluções de escalonamento.
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