A Review of the Enviro-Net Project

📝 Abstract

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.

💡 Analysis

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.

📄 Content

A Review of the Enviro-Net Project∗ November 20, 2021 Gilberto Z. Pastorello1 G. Arturo Sanchez-Azofeifa1 Mario A. Nascimento2 1 Department of Earth and Atmospheric Sciences 1-26 Earth Sciences Buiding University of Alberta T6G 2E3 Edmonton, Alberta, Canada. gilbertozp@acm.org, arturo.sanchez@ualberta.ca 2 Department of Computing Science 2-32 Athabasca Hall University of Alberta T6G 2E8 Edmonton, Alberta, Canada. mario.nascimento@ualberta.ca ∗Text published in: G. Z. Pastorello, G. A. Sanchez-Azofeifa, M. A. Nascimento. Enviro-Net: From Networks of Ground-Based Sensor Systems to a Web Platform for Sensor Data Management. Sensors. 2011. 11(6):6454-6479. doi: 10.3390/s110606454 Abstract Ecosystems monitoring is essential to properly understand their devel- opment and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing sys- tems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deploy- ments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights mon- itoring the conditions in tropical dry forests over long periods of time. 1 arXiv:1106.5489v2 [cs.NI] 30 Jun 2011 This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and anal- ysis. 1 Introduction Monitoring ecosystems at high spatial and temporal resolutions still is a challenging endeavor. Satellite-embarked sensors that offer regular passes support only coarse resolution monitoring and on-demand high resolu- tion satellite or airborne-based monitoring are still too expensive to be considered viable options for frequent data collections. Furthermore, vali- dation of satellite and airborne measurements against the values observed at ground level is often difficult to obtain. Ground-based, or in-situ, sen- sor systems for environmental monitoring have associated challenges as well [1], but have undergone a considerable evolution recently. Such sys- tems are now capable of collecting data at very high temporal resolution for very specific ecosystems through long periods of time. In particular, the use of wireless sensor systems has been shown to be very effective in this type of monitoring [2], from the cost perspective and increasingly in terms of performance and reliability as well. There are many challenges associated with high resolution (both spa- tial and temporal) in-situ environmental monitoring, many of which al- ready well recognized in the literature. Rundel et al. [1], for instance, discuss how these networks generate more data than can be managed by traditional methods for field research data, with data quality assurance and control surpassing capabilities of single individuals dealing with the data, but still being required to produce high-quality data. The large va- riety of problems impacting quality can be more easily detected by using adequate cyberinfratructure for automating the detection, which also al- lows more timely identification of problems in the deployments themselves. They also argue that, although data storage and retrieval is reasonably easy to attain, publishing and sharing data is not as straightforward. Still according to the authors, one of the advantages of this integrated ap- proach for offering data from multiple sensors is the larger world view generated, which is not possible with single sensors—at least not at these spatio-temporal scales. The authors also acknowledge the importance of training scientists in using in-situ monitoring tools, the flexibility of power requirements for these systems (especially wireless) and the use of energy harvesting, problems related gaps in the data (from numerous causes), difficulty to assess precision and fidelity in such systems, and the value of commercial availability for decreasing costs and scaling up deployments sizes. Hart and Martinez [3] discuss power management, large volumes of data and required cyberinfrastructure, beginning of commercial efforts, and data quality control as important issues concerning in-situ environ- mental monitoring. They also raise additional points that require more work, such as assessment of environmental conditions any equipment 2 needs to withstand them (e.g., temperature, pressure, vibration); stan- dardization requirements related to data and metadata representation; security requirements, preventing tampering with both equipment and datasets within the data management systems; and, better means for data interpretation (e.g., by using new methods for data mining). An- other relevant effort can be found in the report from Estrin et al. [4], who focus on cyberinfrastructure. Key points include: the need for better

This content is AI-processed based on ArXiv data.