Towards edge intelligence in smart spaces

After more than two decades of existence, the internet of things has been revolutionizing the way we interact with the world around us. Although, in its origins, the adoption of a cloud computing paradigm supported this ubiquitous computing model, the increasing complexity of IoT systems has led to the gradual fading of the traditional hierarchical model of cloud computing. The search for solutions to the problems of latency, scalability and privacy has, in recent years, driven the movement of data processing and storage, from the cloud, to the edge of the network (edge computing). Starting from the particular case of edge computing that keeps the focus on extending the boundaries of artificial intelligence to the edge of the network - Edge intelligence - a survey of the current state of the art is carried out, culminating into the specification of an architecture to support edge intelligence applications. In order to validate the proposed architecture, two scenarios are presented. In the scope of waste management and energy recycling, a system for used cooking oil classification in a national domestic collection network is presented. With the local classification of the trustworthiness of each deposit, it was possible to significantly shorten the response times, with a direct impact on energy consumption levels. Aimed at smart cities, a second application scenario, proposes an approach based on computer vision and deep learning, for local detection of pedestrians on crosswalks. In this context, an edge intelligence paradigm allowed to overcome privacy related issues, as well as reducing response times by more than 80 times, when compared to a cloud computing based solution.Após mais de duas décadas de existência, a internet das coisas, tem vindo a revolucionar a forma como interagimos com o mundo que nos rodeia. Apesar de, nas suas origens, a adoção de um paradigma de computação em nuvem ter servido de suporte a este modelo de computação ubíqua, a crescente complexidade dos sistemas IoT tem conduzido ao paulatino esvanecer do tradicional modelo hierárquico da computação em nuvem. A procura por soluções para os problemas de latência, escalabilidade e garantia de qualidade de serviço tem, nos últimos anos, impulsionado a deslocação do processamento e armazenamento de dados, da nuvem, para a periferia da rede (computação periférica). Partindo do caso particular de computação periférica que mantém o foco no alargar das fronteiras da inteligência artificial para a periferia da rede - Periferia inteligente - um levantamento do atual estado da arte é levado a cabo, culminando na especificação de uma arquitetura de suporte a cenários de periferia inteligente. Com vista à validação da arquitetura proposta, dois cenários são apresentados. No âmbito da gestão de resíduos e reciclagem energética, um sistema para classificação de óleo alimentar usado, numa rede nacional de recolha doméstica é apresentado. Com classificação local da veracidade de cada depósito foi possível encurtar significativamente os tempos de resposta, com impacto direto nos níveis de consumo energético. Direcionado às cidades inteligentes, um segundo cenário de aplicação, propõe uma abordagem baseada em visão computacional e aprendizagem profunda, para deteção local de peões em passadeiras. Neste contexto, um paradigma de periferia inteligente permitiu ultrapassar questões relativas à privacidade na transmissão de dados, assim como reduzir em mais de 80 vezes os tempos de resposta, quando comparado com uma solução de computação em nuvem

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

State of New Hampshire. Reports, 1905-1906, volume II.- Biennial

Sometimes issued both annually and biennially; Each vol. contains the reports of various departments of the government of the state of New Hampshire; Includes attorneys general\u27s opinion

Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development

The protection and maintenance of environmental resources for future generations require responsible interaction between humans and the environment in order to avoid wasting natural resources. According to an ancient Native American proverb, “We do not inherit the Earth from our ancestors; we borrow it from our children.” This indigenous wisdom has the potential to play a significant role in defining environmental sustainability. Recent technological advances could sustain humankind and allow for comfortable living. However, not all of these advancements have the potential to protect the environment for future generations. Developing societies and maintaining the sustainability of the ecosystem require appropriate wisdom, technology, and management collaboration. This book is a collection of 19 important articles (15 research articles, 3 review papers, and 1 editorial) that were published in the Special Issue of the journal Sustainability entitled “Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development” during 2021-2022.addresses the policymakers and decision-makers who are willing to develop societies that practice environmental sustainability, by collecting the most recent contributions on the appropriate wisdom, technology, and management regarding the different aspects of a community that can retain environmental sustainability