Smart environmental monitoring and assessment technologies (SEMAT)- a new paradigm for low-cost, remote aquatic environmental monitoring

Expense and the logistical difficulties with deploying scientific monitoring equipment are the biggest limitations to undertaking large scale monitoring of aquatic environments. The Smart Environmental Monitoring and Assessment Technologies (SEMAT) project is aimed at addressing this problem by creating an open standard for low-cost, near real-time, remote aquatic environmental monitoring systems. This paper presents the latest refinement of the SEMAT system in-line with the evolution of existing technologies, inexpensive sensors and environmental monitoring expectations. We provide a systems analysis and design of the SEMAT remote monitoring units and the back-end data management system. The system's value is augmented through a unique e-waste recycling and repurposing model which engages/educates the community in the production of the SEMAT units using social enterprise. SEMAT serves as an open standard for the community to innovate around to further the state of play with low-cost environmental monitoring. The latest SEMAT units have been trialled in a peri-urban lake setting and the results demonstrate the system's capabilities to provide ongoing data in near real-time to validate an environmental model of the study site

The integration, analysis and visualization of sensor data from dispersed wireless sensor network systems using the SWE framework

Wireless Sensor Networks (WSNs) have been used in numerous applications to remotely gather real-time data on important environmental parameters. There are several projects where WSNs are deployed in different locations and operate independently. Each deployment has its own models, encodings, and services for sensor data, and are integrated with different types of visualization/analysis tools based on in-dividual project requirements. This makes it difucult to reuse these services for other WSN applications. A user/system is impeded by having to learn the models, encodings, and ser-vices of each system, and also must integrate/interoperate data from different data sources. Sensor Web Enablement (SWE) provides a set of standards (web service interfaces and data encoding/model specifications) to make sensor data publicly available on the web. This paper describes how the SWE framework can be extended to integrate disparate WSN sys-tems and to support standardized access to sensor data. The proposed system also introduces a web-based data visualiza-tion and statistical analysis service for data stored in the Sen-sor Observation Service (SOS) by integrating open source technologies. A performance analysis is presented to show that the additional features have minimal impact on the sys-tem. Also some lessons learned through implementing SWE are discussed

The Integration, Analysis and Visualization of Sensor Data from Dispersed Wireless Sensor Network Systems Using the SWE Framework, Journal of Telecommunications and Information Technology, 2001, nr 4

Wireless Sensor Networks (WSNs) have been used in numerous applications to remotely gather real-time data on important environmental parameters. There are several projects where WSNs are deployed in different locations and operate independently. Each deployment has its own models, encodings, and services for sensor data, and are integrated with different types of visualization/analysis tools based on individual project requirements. This makes it difficult to reuse these services for other WSN applications. A user/system is impeded by having to learn the models, encodings, and services of each system, and also must integrate/interoperate data from different data sources. Sensor Web Enablement (SWE) provides a set of standards (web service interfaces and data encoding/model specifications) to make sensor data publicly available on the web. This paper describes how the SWE framework can be extended to integrate disparate WSN systems and to support standardized access to sensor data. The proposed system also introduces a web-based data visualization and statistical analysis service for data stored in the Sensor Observation Service (SOS) by integrating open source technologies. A performance analysis is presented to show that the additional features have minimal impact on the system. Also some lessons learned through implementing SWE are discussed

Smart Query Answering for Marine Sensor Data

We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks

Internet of Things for Water Sustainability

The water is a finite resource. The issue of sustainable withdrawal of freshwater is a vital concern being faced by the community. There is a strong connection between the energy, food, and water which is referred to as water-food-energy nexus. The agriculture industry and municipalities are struggling to meet the demand of water supply. This situation is particularly exacerbated in the developing countries. The projected increase in world population requires more fresh water resources. New technologies are being developed to reduce water usage in the field of agriculture (e.g., sensor guided autonomous irrigation management systems). Agricultural water withdrawal is also impacting ground and surface water resources. Although the importance of reduction in water usage cannot be overemphasized, major efforts for sustainable water are directed towards the novel technology development for cleaning and recycling. Moreover, currently, energy technologies require abundant water for energy production. Therefore, energy sustainability is inextricably linked to water sustainability. The water sustainability IoT has a strong potential to solve many challenges in water-food-energy nexus. In this chapter, the architecture of IoT for water sustainability is presented. An in-depth coverage of sensing and communication technologies and water systems is also provided

From polyps to pixels: understanding coral reef resilience to local and global change across scales

Abstract Context Coral reef resilience is the product of multiple interacting processes that occur across various interacting scales. This complexity presents challenges for identifying solutions to the ongoing worldwide decline of coral reef ecosystems that are threatened by both local and global human stressors. Objectives We highlight how coral reef resilience is studied at spatial, temporal, and functional scales, and explore emerging technologies that are bringing new insights to our understanding of reef resilience. We then provide a framework for integrating insights across scales by using new and existing technological and analytical tools. We also discuss the implications of scale on both the ecological processes that lead to declines of reefs, and how we study those mechanisms. Methods To illustrate, we present a case study from Kāneʻohe Bay, Hawaiʻi, USA, linking remotely sensed hyperspectral imagery to within-colony symbiont communities that show differential responses to stress. Results In doing so, we transform the scale at which we can study coral resilience from a few individuals to entire ecosystems. Conclusions Together, these perspectives guide best practices for designing management solutions that scale from individuals to ecosystems by integrating multiple levels of biological organization from cellular processes to global patterns of coral degradation and resilience

Development and characterisation of a self-powered measurement buoy prototype by means of piezoelectric energy harvester for monitoring activities in a marine environment

In the interest of our society, for example in Smart City but also in other specific backgrounds, environmental monitoring is an essential activity to measure the quality of different ecosystems. In fact, the need to obtain accurate and extended measurements in space and time has considerably become relevant. In very large environments, such as marine ones, technological solutions are required for the use of smart, automatic, and self-powered devices in order to reduce human maintenance service. This work presents a simple and innovative layout for a small self-powered floating buoy, with the aim of measuring and transmitting the detected data for visualization, storage and/or elaboration. The power supply was obtained using a cantilever harvester, based on piezoelectric patches, converting the motion of ripple waves. Such type of waves is characterized by frequencies between 1.50 Hz and 2.50 Hz with oscillation between 5.0 ° and 7.0 °. Specifically, a dedicated experimental setup was created to simulate the motion of ripple waves and to evaluate the suitability of the proposed design and the performance of the used harvester. Furthermore, a dynamic analytical model for the harvester has been defined and the uncertainty correlated to the harvested power has been evaluated. Finally, the harvested voltage and power have shown how the presented buoy behaves like a frequency transformer. Hence, although the used cantilever harvester does not work in its resonant frequency, the harvested electricity undergoes a significant increase.</p

Middleware for plug and play integration of heterogeneous sensor resources into the sensor web

The study of global phenomena requires the combination of a considerable amount of data coming from different sources, acquired by different observation platforms and managed by institutions working in different scientific fields. Merging this data to provide extensive and complete data sets to monitor the long-term, global changes of our oceans is a major challenge. The data acquisition and data archival procedures usually vary significantly depending on the acquisition platform. This lack of standardization ultimately leads to information silos, preventing the data to be effectively shared across different scientific communities. In the past years, important steps have been taken in order to improve both standardization and interoperability, such as the Open Geospatial Consortium’s SensorWeb Enablement (SWE) framework. Within this framework, standardized models and interfaces to archive, access and visualize the data from heterogeneous sensor resources have been proposed. However, due to the wide variety of software and hardware architectures presented by marine sensors and marine observation platforms, there is still a lack of uniform procedures to integrate sensors into existing SWE-based data infrastructures. In this work, a framework aimed to enable sensor plug and play integration into existing SWE-based data infrastructures is presented. First, an analysis of the operations required to automatically identify, configure and operate a sensor are analysed. Then, the metadata required for these operations is structured in a standard way. Afterwards, a modular, plug and play, SWE-based acquisition chain is proposed. Finally different use cases for this framework are presented.Peer ReviewedPostprint (published version