Edge Computing for Cattle Behavior Analysis

peer reviewedSmartphones, particularly iPhone, can be relevantinstruments for researchers because they are widely used aroundthe world in multiple domains of applications such as animalbehavior. iPhone are readily available on the market, containmany sensors and require no hardware development. They areequipped with high performance inertial measurement units(IMU) and absolute positioning systems analyzing user’s move-ments, but they can easily be diverted to analyze likewise thebehaviors of domestic animals such as cattle. Using smartphonesto study animal behavior requires the improvement of theautonomy to allow the acquisition of many variables at a highfrequency over long periods of time on a large number ofindividuals for their further processing through various modelsand decision-making tools. Indeed, storing, treating data at theiPhone level with an optimal consumption of energy to maximizebattery life was achieved by using edge computing on the iPhone.This processing reduced the size of the raw data by 42% onaverage by eliminating redundancies. The decrease in samplingfrequency, the selection of the most important variables andpostponing calculations to the cloud allowed also an increasein battery life by reducing of amount of data to transmit. Inall these use cases, the lambda architectures were used to ingeststreaming time series data from the Internet of Things. Cattle,farm animals’ behavior consumes relevant data from InertialMeasurement Unit (IMU) transmitted or locally stored on thedevice. Data are discharged offline and then ingested by batchprocessing of the Lambda Architecture

Forests

In this paper, we provide an overview of positioning systems for moving resources in forest and fire management and review the related literature. Emphasis is placed on the accuracy and range of different localization and location-sharing methods, particularly in forested environments and in the absence of conventional cellular or internet connectivity. We then conduct a second review of literature and concepts related to several emerging, broad themes in data science, including the terms |, |, |, |, |, |, and |. Our objective in this second review is to inform how these broader concepts, with implications for networking and analytics, may help to advance natural resource management and science in the future. Based on methods, themes, and concepts that arose in our systematic reviews, we then augmented the paper with additional literature from wildlife and fisheries management, as well as concepts from video object detection, relative positioning, and inventory-tracking that are also used as forms of localization. Based on our reviews of positioning technologies and emerging data science themes, we present a hierarchical model for collecting and sharing data in forest and fire management, and more broadly in the field of natural resources. The model reflects tradeoffs in range and bandwidth when recording, processing, and communicating large quantities of data in time and space to support resource management, science, and public safety in remote areas. In the hierarchical approach, wearable devices and other sensors typically transmit data at short distances using Bluetooth, Bluetooth Low Energy (BLE), or ANT wireless, and smartphones and tablets serve as intermediate data collection and processing hubs for information that can be subsequently transmitted using radio networking systems or satellite communication. Data with greater spatial and temporal complexity is typically processed incrementally at lower tiers, then fused and summarized at higher levels of incident command or resource management. Lastly, we outline several priority areas for future research to advance big data analytics in natural resources.U01 OH010841/OH/NIOSH CDC HHSUnited States/U54 OH007544/OH/NIOSH CDC HHSUnited States

Pet sense: sistema de monitorização de animais em hospitalização

The observation and treatment of animals in veterinary hospitals is still very dependent on manual procedures, including the collection of vital signs (temperature, heart rate, respiratory rate and blood pressure). These manual procedures are time-consuming and invasive, affecting the animal’s well-being. In this work, we purpose the use of IoT technologies to monitor animals in hospitalization, wearing sensors to collect vitals, and low-cost hardware to forward them into a cloud backend that analyses and stores data. The history of observed vitals and alarms can be accessed in the web, included in the Pet Universal software suite. The overall architecture follows a stream processing approach, using telemetry protocols to transport data, and Apache Kafka Streams to analyse streams and trigger alarms on potential hazard conditions. The system was fully implemented, although with laboratory sensors to emulate the smart devices to be worn by the animals. We were able to implement a data gathering and processing pipeline and integrate with the existing clinical management information system. The proposed solution can offer a practical way for long-term monitoring and detect abnormal values of temperature and heart rate in hospitalized animals, taking into consideration the characteristics of the monitored individual (species and state).A observação e tratamento de animais hospitalizados continua muito dependente de procedimentos manuais, especialmente no que diz respeito à colheita de sinais vitais (temperatura, frequência cardíaca, frequência respiratória e pressão arterial). Estes procedimentos manuais são dispendiosos em termos de tempo e afetam o bem-estar do animal. Neste projeto, propomos o recurso a tecnologias IoT para monitorizar animais hospitalizados equipados com sensores que medem sinais vitais, com hardware acessível, e envio dos dados para um serviço na cloud que os analisa e armazena. O histórico dos valores e alarmes podem ser acedidos na web e incluídos na plataforma comercial da Pet Universal. A arquitetura geral segue uma abordagem de processamento funcional, usando protocolos de telemetria para transportar dados e Apache Kafka Streams, analisando e lançando alarmes sobre potenciais condições de risco de acordo com a temperatura e pulsação. O sistema foi totalmente implementado, embora com sensores de laboratório para simular os dispositivos a serem usados pelos animais. Conseguimos implementar um circuito de colheita e processamento de dados e integrar com o sistema de gestão clínica já existente. A solução proposta oferece uma forma prática de monitorização continuada e de deteção de valores anormais de temperatura e frequência cardíaca em animais hospitalizados, tomando em conta as características do indivíduo monitorado (espécie e estado).Mestrado em Engenharia Informátic

The potential of smartphone apps to collect self-recorded data in agricultural households : a study on time-use in Zambia

Mobile information and communication technologies (ICTs) have spread across the developing world and are used increasingly by smallholder farmers. While the potential of ICTs, such as smartphone applications, to provide new opportunities for agricultural development is widely acknowledged, the potential to use them as research tools has not been explored. This thesis assesses the potential of smartphone applications for the collection of data from agricultural households in developing countries. Can smartphone applications that use visual tools be used for self-recording of data by the respondents themselves where literacy levels are low? Can such smartphone applications that allow for real-time data recording increase the accuracy of the collected data? Answering these questions is important as, so far, data from agricultural households are usually collected using surveys, which are prone to recall biases. This is a problem, as researchers, policymakers and development practitioners need reliable data for their work. Poor data can lead to misguided policy recommendations and actions with adverse effects on vulnerable population groups. This can lead to agricultural development trajectories that are socially unequal and unsustainable. To assess the potential of smartphone apps to collect self-recorded data, a smartphone application called Timetracker was developed as part of this thesis. The Timetracker allows study respondents to record data in real time with the help of illustrations. Recording data in real time reduces recall bias, and using pictures ensures that participants with low literacy can use the application. In its current form, the Timetracker can be used to collect data on time-use and nutrition. Collecting reliable data on time-use and nutrition is key for various strands of research. For example, time-use data are needed to calculate labor productivity and analyze how productivity is affected by new technologies. Time-use data can also help reveal gender-based power relations and asymmetries by pointing out unpaid domestic work. Similarly, nutritional data are crucial for various academic fields and debates. For example, nutritional data are needed to explore the factors determining food and nutrition security, to study how farm diversity affects consumption diversity and to monitor food and nutrition policies and programs. This study is based on three main chapters, which reflect the main objectives of the whole thesis: 1) to explore and test whether smartphone applications can be used to collect data from rural households in developing countries focusing on time-use and nutrition data, 2) to assess the accuracy of data collected with smartphone applications vis-à-vis recall-based data collection methods, and 3) to use the data to understand the effects of agricultural mechanization on the intrahousehold allocation of time-use within smallholder farming households in Zambia. The first two chapters have a primarily methodological focus. The last chapter is an empirical study. This thesis concludes that in addition to improving the accuracy of socioeconomic data collection, smartphone applications may open new research pathways, including through the opportunities provided by real-time data collection and by combining self-recorded data with sensor-recorded data, which may open interesting transdisciplinary research pathways. This thesis suggests that there is a large and still untapped potential for using smartphone applications to collect data on complex agricultural systems in the digital age.Mobile Informations- und Kommunikationstechnologien (IKT) werden zunehmend auch von Kleinbauern in Entwicklungsländern eingesetzt. Während das Potenzial von IKT, wie Smartphone-Anwendungen, neue Möglichkeiten für die landwirtschaftliche Entwicklung zu bieten, weithin anerkannt ist, wurde deren Potenzial als Forschungsinstrumente bislang kaum erforscht. Diese Dissertation untersucht das Potenzial von Smartphone-Anwendungen zur Erfassung sozioökonomischer Daten von landwirtschaftlichen Haushalten in Entwicklungsländern. Können Smartphone-Anwendungen, die visuelle Elemente verwenden, für die Selbstaufzeichnung von Daten durch Befragte verwendet werden, selbst wenn deren Alphabetisierung gering ist? Können solche Smartphone-Anwendungen, mit denen Daten in Echtzeit erfasst werden, die Genauigkeit der erfassten Daten erhöhen? Die Beantwortung dieser Fragen ist wichtig, da die Daten von landwirtschaftlichen Haushalten bisher üblicherweise durch Haushaltsbefragungen erhoben werden, die häufig durch Erinnerungsverzerrungen beinflusst sind. Dies ist ein Problem, da Forscher, politische Entscheidungsträger und Entwicklungsakteure verlässliche Daten für ihre Arbeit benötigen. Unzureichende Daten können zu falschen Politikempfehlungen und Politkmaßnahmen führen, die sich negativ auf bestimmte Bevölkerungsgruppen auswirken können. Dies kann zu landwirtschaftlichen Entwicklungspfaden führen, die sozial ungleich und nicht nachhaltig sind. Um das Potenzial von Smartphone-Apps zur Selbstaufzeichnung von Daten durch Befragte zu bewerten, wurde im Rahmen dieser Dissertation eine Smartphone-Anwendung namens Timetracker entwickelt. Der Timetracker ermöglicht es den Befragten, Daten anhand von Abbildungen in Echtzeit zu erfassen. Das Aufzeichnung von Daten in Echtzeit verringert Erinnerungsverzerrungen und die Verwendung von Bildern stellt sicher, dass Teilnehmer mit geringer Alphabetisierung die Anwendung verwenden können. In seiner jetzigen Form kann der Timetracker verwendet werden, um Daten zu Zeitnutzung und Ernährung zu sammeln. Zuverlässiger Daten zu Zeitnutzung und Ernährung sind essenziell für verschiedene Forschungsbereiche. Zum Beispiel werden Daten zur Zeitnutzung benötigt, um Arbeitsproduktivität zu berechnen und zu analysieren, wie die Produktivität durch neue Technologien beeinflusst wird. Daten zur Zeitnutzung können auch helfen, geschlechtsspezifische Machtverhältnisse und Asymmetrien aufzuzeigen, indem sie auf unbezahlte häusliche Arbeiten hinweisen. In ähnlicher Weise sind Ernährungsdaten für verschiedene akademische Bereiche von entscheidender Bedeutung. Ernährungsdaten sind beispielsweise erforderlich, um die Faktoren zu untersuchen, die die Ernährungssicherheit bestimmen; um zu untersuchen, wie die Diversität der landwirtschaftlichen Betriebe die Nahrungskonsumvielfalt beeinflusst; und um die Ernährungsstrategien und -programme zu überwachen. Die Studie basiert auf drei Hauptkapiteln, welche die Hauptfragen der gesamten Dissertation widerspiegeln: 1) zu untersuchen, ob Smartphone-Anwendungen verwendet werden können, um Daten wie Zeitnutzung und Ernährung von ländlichen Haushalten in Entwicklungsländern zu sammeln; 2) zu beurteilen wie genau die mit Smartphone-Anwendungen erfassten Daten im Vergleich zu auf Erinnerung basierenden Datenerhebungsmethoden sind; 3) unter Verwendung der gesammelten Daten zu analysieren, wie sich landwirtschaftliche Mechanisierung auf die Zeitaufteilung innerhalb von kleinbäuerlichen Haushalten in Sambia auswirkt. Die ersten beiden Kapitel sind primär methodisch ausgerichtet. Das letzte Kapitel ist dann eine empirische Studie. Die Dissertation kommt zu dem Schluss, dass Smartphone-Anwendungen nicht nur die Genauigkeit der Erfassung sozioökonomischer Daten verbessern, sondern auch neue Forschungspfade eröffnen. Die geschieht vor allem durch die Möglichkeiten der Echtzeit-Datenerfassung und durch die Kombination selbst erfasster Daten mit sensoraufgezeichneten Daten, was interessante transdisziplinäre Forschungsmöglichkeiten aufzeigt. Die Dissertation legt nahe, dass es ein großes und noch nicht ausgeschöpftes Potenzial gibt, Smartphone-Anwendungen zum Sammeln von Daten zu komplexen landwirtschaftlichen Systemen in Entwicklungsländern im digitalen Zeitalter zu nutzen

Internet of Things. Information Processing in an Increasingly Connected World

This open access book constitutes the refereed post-conference proceedings of the First IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2018, held at the 24th IFIP World Computer Congress, WCC 2018, in Poznan, Poland, in September 2018. The 12 full papers presented were carefully reviewed and selected from 24 submissions. Also included in this volume are 4 WCC 2018 plenary contributions, an invited talk and a position paper from the IFIP domain committee on IoT. The papers cover a wide range of topics from a technology to a business perspective and include among others hardware, software and management aspects, process innovation, privacy, power consumption, architecture, applications

Smart farming : concepts, applications, adoption and diffusion in southern Brazil

Smart Farming (SF) is a modern set technologies that can be used to improve decision making and automation throughout agricultural activities. To accomplish this, some farmers are using the Internet of Things (IoT), which is new technology that allows objects to be sensed or controlled remotely across existing network infrastructures. Further, it can create opportunities for more direct integration of the physical world into computer-based systems, which can result in improved efficiency, accuracy, and economic benefits for SF users. Besides the new areas such as IoT, Cloud Computing, Cognitive Computing and Big Data, two fields have contributed to the development of SF: Precision Agriculture (PA) and Information Technology (IT). The present study analyzed SF’s innovative processes, beginning with the production of scientific knowledge through to SF’s final diffusion of these technologies into agriculture. The discussion and analysis are based on the theoretical contributions of the evolutionary economy and the techno-economic paradigms and were used to analyze technological revolutions. The work consisted of three distinct methodological steps First, to better understand the subject being studied, interviews were conducted with researchers and market professionals, from different areas, such as agriculture, electronics engineering and mechanization. During the second stage, text mining was used to analyze scientific literature on SF. In the third step an empirical research was carried out to analyze the adoption of SF technologies in real environment. To operationalize this step, a questionnaire was sent to grain farmers from the southern region of Brazil, which included Paraná, Santa Catarina, and Rio Grande do Sul. Since these grain' farmers produced 50% or more of the gross revenue in grains were included in the database. After the surveys were completed, the empirical data was used to analyze the adoption of these technologies. Based on the results, it was possible to infer that SF technologies are in the process of gestation and emergence. There has been intense scientific development in technologies, such as IoT and smart environments. Additionally, there has been a strong spillover effect from industries to agriculture. Because of this, it is expected that the number of SF innovations available to the market will grow over the next several years The study indicated main factors that a farmer chose to adopt SF were: potential increase in productivity, better process quality, cost reduction, and a greater knowledge of cultivated areas. Additionally, adding in these factors, education had the positive effect on the adoption of georeferenced soil sampling. The adoption of an autopilot spray pilot and management software was positively influenced by the size of the area. The results of the study have indicated that a higher level of schooling tends to increase the probability of adopting these technologies. It was also found that high equipment costs, the low qualification of rural workers, the precariousness of Internet access in Brazilian rural regions, and the need to insert a lot of data and information in specific programs available to take advantage of SF technologies are the main barriers faced by grain producers, which contribute to their delay in implementing SF technologies. Additionally, it has been verified that the machines used in the grain production systems are becoming digitalized—the availability of equipment with sensors and automated processes are rapidly increasing. However, from the famers’ perception, many technicians and consultants, such as agronomists and agricultural engineers, have not yet adapted to the new context of agriculture, with growing implementation of SF technologies amongst farmers. Thus, the question remains whether farmers and technical consultants can take advantage of available SF technologies and, if so, whether they can use these technologies to help them make decisions and monitor their farming practices. The results of this research can be used to further understand how SF technologies are being used among Brazilian grain producers.O Smart Farming (SF) é um novo conjunto de tecnologias que podem ser usadas para melhorar a tomada de decisões e a automação em atividades agrícolas. Para isso, alguns agricultores começaram a utilizar a Internet das Coisas (IoT), que é uma tecnologia que permite que os objetos sejam detectados ou controlados remotamente em infraestruturas de rede existentes. Esse processo tende a criar oportunidades para uma integração mais direta do mundo físico com sistemas baseados em computador, gerando maior eficiência, precisão e benefícios econômicos para os usuários de SF. Além das novas áreas como IoT, Computação em Nuvem, Cognitive Computing e Big Data, dois campos contribuíram para o desenvolvimento de SF: Agricultura de Precisão (AP) e Tecnologia da Informação (TI).A presente tese analisou o processo de inovação no contexto da SF, desde a produção de conhecimento científico até a fase de difusão dessas tecnologias na agricultura, sendo que, o objeto de estudo contemplou as propriedades rurais de grãos. A discussão e análise realizadas no trabalho têm como base teórica o aporte da economia evolucionária e o paradigma tecnoeconômico usado para analisar revoluções tecnológicas. O trabalho consistiu de três etapas metodológicas distintas A primeira, de caráter exploratório, foi realizada por meio de entrevistas com especialistas de diferentes áreas, visando melhor compreender o tema estudado. Na segunda etapa, realizou-se um levantamento na literatura científica acerca do tema. De posse dessas informações, operacionalizou-se uma pesquisa empírica para analisar a adoção dessas tecnologias no ambiente real. Para isso, foram aplicados 119 questionários com produtores de grãos da região Sul do Brasil (Paraná, Santa Catarina e Rio Grande do Sul), sendo adotada amostragem estratificada, pois foram considerados produtores cujas propriedades produzissem 50% ou mais da receita bruta em grãos.Com base nos resultados, foi possível inferir que as tecnologias de SF encontram-se no processo de gestação e emergência. Observou-se um intenso desenvolvimento científico em tecnologias como IoT e ambientes inteligentes, bem como um forte efeito de "spillover" de outras indústrias para a agricultura. Entretanto, espera-se que nos próximos anos, o número de inovações disponíveis ao mercado na área de SF cresça. Os principais fatores de adoção de SF observados no trabalho foram: a) aumento de produtividade, b) melhor qualidade de processo, c) redução de custos, e d) maior conhecimento de áreas cultivadas. Da mesma forma, alguns fatores aumentaram a adoção de tecnologias em diferentes intensidades e maneiras. A educação teve o efeito significativo e positivo na adoção de tecnologias georeferenciadas de amostragem de solo A adoção do piloto de pulverização do piloto automático e softwares de gerenciamento teve influência positiva do tamanho da área. Os resultados da tese sinalizaram que um maior grau de escolaridade, tende a aumentar probabilidade de adoção dessas tecnologias. As principais barreiras que atrasam a entrada dos produtores de grãos na SF foram: a) o preço dos equipamentos, b) baixa qualificação do trabalho rural c) a precariedade do acesso à Internet nas regiões rurais brasileiras, e d) necessidade de inserir muitos dados e informações em software. Verificou-se assim que as máquinas empregadas nos sistemas produtivos de grãos estão passando pelo processo de digitalização, especialmente pelo aumento da disponibilidade de equipamentos com sensores e processos automatizados. No entanto, na percepção do produtor rural, grande número de técnicos e consultores ainda não está adaptado ao novo contexto da agricultura. Com isso, permanece o questionamento acerca da capacidade do produtor e dos consultores técnicos de acompanhar e aproveitar o potencial das tecnologias de SF na tomada de decisão na propriedade rural. Os resultados desse trabalho, inéditos no contexto brasileiro, avançam no sentido de compreender a difusão da SF no contexto brasileiro

Drones and Geographical Information Technologies in Agroecology and Organic Farming

Although organic farming and agroecology are normally not associated with the use of new technologies, it’s rapid growth, new technologies are being adopted to mitigate environmental impacts of intensive production implemented with external material and energy inputs. GPS, satellite images, GIS, drones, help conventional farming in precision supply of water, pesticides, fertilizers. Prescription maps define the right place and moment for interventions of machinery fleets. Yield goal remains the key objective, integrating a more efficient use or resources toward an economic-environmental sustainability. Technological smart farming allows extractive agriculture entering the sustainability era. Societies that practice agroecology through the development of human-environmental co-evolutionary systems represent a solid model of sustainability. These systems are characterized by high-quality agroecosystems and landscapes, social inclusion, and viable economies. This book explores the challenges posed by the new geographic information technologies in agroecology and organic farming. It discusses the differences among technology-laden conventional farming systems and the role of technologies in strengthening the potential of agroecology. The first part reviews the new tools offered by geographic information technologies to farmers and people. The second part provides case studies of most promising application of technologies in organic farming and agroecology: the diffusion of hyperspectral imagery, the role of positioning systems, the integration of drones with satellite imagery. The third part of the book, explores the role of agroecology using a multiscale approach from the farm to the landscape level. This section explores the potential of Geodesign in promoting alliances between farmers and people, and strengthening food networks, whether through proximity urban farming or asserting land rights in remote areas in the spirit of agroecological transition. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons 4.0 license

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains