A new paradigm for integrated environmental monitoring

Abstract

The vision of an integrated Earth observation system to help protect and sustain the planet and its inhabitants is significant and timely, and thus has been identified recently by many organizations. Clearly, the societal benefits of global integrated monitoring are many: to understand how environment and humans are linked, to protect and monitor resources (water supply, weather, oceans) and predict and adapt to their change, to provide for sustainable development, and to reduce costs/impacts of disasters and provide for an effective and intelligent response.The requirements of such a system are that it be able to collect observations (remote sensing/satellite data and in-situ sensors), manage data 1,3 (archive, model), interface with users (user-and context-specific display), and that it enhance human capacity by providing for research/training, collaboration and ultimately decision support. Further, in order to be effective, it must also be easily usable by a wide cross section of users, provide for advanced analysis and visualization with interaction and collaboration tools over the Internet; be open source, protocol, and information; and future-proof, modular and extendable as new needs and technologies arise.Intelesense Technologies was spun off from Stanford University to provide worldwide integrated monitoring of the environment and its' inhabitants, to understand their interrelationships and improve our ability to protect the planet and its people. A global network of wireless sensor devices transmit their data to gridbased computing servers where they are integrated with hundreds of thousands of other data sources to help to better understand their interrelationships. This data, along with thousands of sources from NASA, USGS, Google, and others are provided within a federated, open system of systems, with a collaborative, worldwide GIS portal to provide interactive exploration of the world and its data. The goal is to collaborate across government, academia, and with industrial partners to empower the researcher, scientist, and policymaker with data, analysis, and information leading to a better understanding.

Cloud Computing in natural hazard modeling systems: Current research trends and future directions

“…The need of real-time capabilities to solve data-intensive problems and offer on-demand services to a dynamic number of end users in traffic management and surveillance was addressed by Li et al [35] by using Cloud Computing. The inherent challenges of ecology in regard to storage, scalability, platform integration and deployment were addressed by the use of Cloud Computing in conjunction with Geospatial Science [36]. The Cloud Computing also facilitated the support for ensemble runs for predicting and forecasting the availability of freshwater and spread of different natural hazards [37].…”

“…Moreover, the system classified the data into different levels based on severity and fatalities of the flood. The environmental monitoring developed by Montgomery et al [36] performed various processing of Geospatial data for prediction of the changes in various environmental resources so as to ensure proper adaptation for sustainability. Li et al [35] used Cloud infrastructure to perform various complex Geospatial computing tasks such as FCD query, FCD map matching and speed computation for roadlinks for urban traffic monitoring.…”

“…They used the Google Map API and interactive combination of color codes to represent data under different categories for concise and useful information related to the floods. Montgomery et al [36] integrated a collaborative visualization along with mapping tools in the user interface of the system for visualization of data for monitoring. The traffic surveillance system described by Li et al [35] evaluated the utility of Cloud Computing for visualization of urban traffic data obtained after computing tasks namely Floating Car data (FCD) query, FCD map matching and speed computation for road links using different interactive map tools.…”

Wavelet Study of Meteorological Data Collected by Arduino-Weather Station: Impact on Solar Energy Collection Technology

“…More precisely, it has been employed the MODBUS protocol to establish a communication between the weather station and the microcontroller to read and write the data [20,21]. In Fig.…”

Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

“…To understand, protect and improve our living environment, humans have been accumulating valuable records about the changes occurring for thousands of years or longer. The records are obtained through various sensing technologies, including our human eyes, touch and feel, and more recently, satellites, telescopes, in situ sensors and sensor webs (Montgomery and Mundt 2010). The advancements of sensing technologies have dramatically improved the accuracy and spatiotemporal scope of the records.…”