209,929 research outputs found

    WSN infrastructure for green campus development

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    A system providing accurate environmental data for campus stakeholders to formulate and evaluate policies of the sustainable campus development is needed. This paper presents the design of WSN infrastructure capable of providing accurate, real-time and reliable environment data, namely PM2.5, SO2, CO, O3, NO2, temperature, humidity, soil moisture and light intensity to be analyzed and presented by servers. This infrastructure is composed of fixed sensor nodes, mobile sensor nodes, display nodes and server nodes. The sensor node provides environment raw data to the server using an RF transceiver. The server processes, stores and presents environment information to public users through Internet and mobile network. This infrastructure can be used as a platform to provide environmental data to decision support system for campus stakeholders, so that a recommendation can be made

    A Perfect Storm: Environmental Justice and Air Quality Impacts of Offshore Oil and Gas Development in the Arctic Outer Continental Shelf

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    The Arctic Outer Continental Shelf is the next great legal battleground over oil and gas resources, environmental protection, and environmental justice.  The Arctic is home to an array of sensitive ecological resources and a large Native Alaskan population that relies heavily on the natural environment for food and supplies.  The Arctic Ocean also holds a vast amount of untapped oil and gas resources that had previously been largely inaccessible because of harsh climatic conditions and withdrawals of large swaths of the Shelf by Congress and multiple presidents.  However, climate change is melting Arctic sea ice and opening up previously inaccessible areas.  In addition, President Trump is pushing to expand oil and gas development everywhere, including the Arctic.  If President Trump’s plans prevail against the many legal challenges seeking to protect the Arctic, Native Alaskans will face a multitude of threats to their health, safety, and way of life.Scholars, journalists, and environmental groups have already illuminated the threats of oil spills and climate change.  This Comment focuses on a less discussed impact of offshore oil and gas development: air pollution and its effects on Native Alaskans.  Onshore oil and gas development has already been polluting the air of Alaskan communities, causing increases in respiratory illnesses and other health problems, and leading to climate change, which is disrupting the natural environment upon which Native Alaskans depend for food and supplies.  A new era of offshore development would amplify these problems and create new and unique challenges that disproportionately burden Native Alaskan communities.This Comment makes two novel contributions.  First, it illuminates the erratic history and disjointed nature of air quality regulation on the Outer Continental Shelf.  Second, this Comment highlights how the federal government’s current regulatory structure for offshore air emissions uniquely fails Native Alaskans who are seeking to protect their health and way of life.  In addition, this Comment makes some recommendations for statutory and regulatory changes to better address the environmental justice impacts of air pollution from offshore oil and gas development in the Arctic

    Mobile Air Quality Studies (MAQS) - an international project

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    Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"- exposure in relation to non-"traffic zone"-exposure. Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including including NO2, SO2, nanoparticles, and ozone

    Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).

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    In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena

    From Sensor to Observation Web with Environmental Enablers in the Future Internet

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    This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

    How will the Internet of Things enable Augmented Personalized Health?

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    Internet-of-Things (IoT) is profoundly redefining the way we create, consume, and share information. Health aficionados and citizens are increasingly using IoT technologies to track their sleep, food intake, activity, vital body signals, and other physiological observations. This is complemented by IoT systems that continuously collect health-related data from the environment and inside the living quarters. Together, these have created an opportunity for a new generation of healthcare solutions. However, interpreting data to understand an individual's health is challenging. It is usually necessary to look at that individual's clinical record and behavioral information, as well as social and environmental information affecting that individual. Interpreting how well a patient is doing also requires looking at his adherence to respective health objectives, application of relevant clinical knowledge and the desired outcomes. We resort to the vision of Augmented Personalized Healthcare (APH) to exploit the extensive variety of relevant data and medical knowledge using Artificial Intelligence (AI) techniques to extend and enhance human health to presents various stages of augmented health management strategies: self-monitoring, self-appraisal, self-management, intervention, and disease progress tracking and prediction. kHealth technology, a specific incarnation of APH, and its application to Asthma and other diseases are used to provide illustrations and discuss alternatives for technology-assisted health management. Several prominent efforts involving IoT and patient-generated health data (PGHD) with respect converting multimodal data into actionable information (big data to smart data) are also identified. Roles of three components in an evidence-based semantic perception approach- Contextualization, Abstraction, and Personalization are discussed
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