A Novel Low-Cost Open-Hardware Platform for Monitoring Soil Water Content and Multiple Soil-Air-Vegetation Parameters

Bitella, Giovanni; Rossi, Roberta; Bochicchio, Rocco; Perniola, Michele; Amato, Mariana

doi:10.3390/s141019639

Cited by 85 publications

(50 citation statements)

References 53 publications

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“…mental monitoring (e.g., Bitella et al, 2014;Lopez and Villaruz, 2015), field applications spanning extreme conditions or longer time periods are rare. In this research letter, we present our advances in the development of a low-cost Arduino-based datalogger toward establishing a hydrologic monitoring network in a data-scarce region of the tropics, and share the challenges faced and successes obtained with this new technology over a monitoring period of nearly 2 yr.…”

Section: Core Ideasmentioning

confidence: 99%

Developing a Hydrologic Monitoring Network in Data‐Scarce Regions Using Open‐Source Arduino Dataloggers

Hund

Johnson

Keddie

2016

Agricultural & Env Letters

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Core Ideas An innovative low‐cost open‐source Arduino‐based datalogger was developed. The datalogger was deployed for hydrologic monitoring in tropical watersheds. Arduino datalogger performance was robust after overcoming initial challenges. The system has great potential for automated continuous environmental monitoring. Continuous hydrologic monitoring is limited in many regions of the world, creating serious knowledge gaps for water resources managers and scientists. Recent advances in open‐source software and hardware technologies, such as the Arduino project, show potential for the development of low‐cost (∼$100) automated dataloggers required for continuous data collection. We developed an Arduino‐based datalogger (the Ecohydro Logger) coupled with water sensors providing digital output to establish a hydrologic monitoring network in the data‐scarce wet‐dry tropics of Guanacaste, Costa Rica. While we experienced some challenges with a first iteration of our Arduino‐based datalogger, an improved version was robust and able to capture long periods of high‐frequency stream discharge data. Integration of the monitoring program into the local community was also key to successful deployment, allowing exchange of local knowledge and support. The accessible and low‐cost nature of Arduino‐based dataloggers can provide a means to extend continuous environmental monitoring into data‐scarce regions.

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Section: Core Ideasmentioning

confidence: 99%

Developing a Hydrologic Monitoring Network in Data‐Scarce Regions Using Open‐Source Arduino Dataloggers

Hund

Johnson

Keddie

2016

Agricultural & Env Letters

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“…Thanks to the GPS connection granted by the installation of the on-board ArduinoGSMShield® [26]; all the monitored data together with the GPS position of the station can be transmitted to the central server-side. Here the data are firstly stored in a remote measures database and secondly used for model simulations and georeferentiation.…”

Section: B Biosensors For Edcs Sensingmentioning

confidence: 99%

“…The DPU unit, is composed by an amplification stage and a frequency analyser: this stage will be implemented on an embedded ArduinoMEGA® microcontroller-board [26].…”

Section: B Biosensors For Edcs Sensingmentioning

confidence: 99%

A biosensored spatial data infrastructure for the dynamic monitoring of the presence and the activity of endocrine disrupting chemicals in water

Vito¹

2015

Third International Conference on Advances in Bio-Informatics and Environmental Engineering - ICABEE 2015

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Abstract-Endocrine disrupting chemicals (EDCs) are a subset of environmental contaminants that can produce adverse developmental, reproductive, neurological, and immune effects in both humans and wildlife. EDCs have been reported to have a ubiquitous presence in the environment and in particular aquatic ecosystems. Many EDCs, in fact are not completely removed with conventional wastewater treatment systems. Due to their harmfulness and ubiquity, since the 1990's a number of countries, multinational governments such as the European Union and inter-government organizations (Organization for Economic Cooperation and Development, OECD) have initiated or amended programs to integrate EDCs into current strategies to assess chemical safety. These programs has been mainly focused on regulate exposure to EDCs, neglecting the issues about monitoring. Conventional water monitoring processes involves the collection of water samples that only provide snapshots of the situation at the sampling site and time, rather than information on spatiotemporal variations in water characteristics. Biosensors indeed, -defined by IUPAC as a "self-contained integrated device that is capable of providing specific analytical information using a biological recognition element" -offer the possibility for a faster and timely measurement for pollutants in water.Biosensors can be combined with remote communication technology like GPS and GPRS, resulting in networks of distributed elements able to gather spatial and temporal information. These sensing networks can be integrated with spatial data infrastructures. Spatial data infrastructures (SDI) are a framework of technologies, policies, and institutional arrangements includes all the technologies like Geographical Information Systems (GIS), geoportals and diffuse georeferred tools that enable the sharing of geospatial information on a national, regional or global level. SDI can be useful for water monitoring because can handle data and models providing spatial and temporal information on pollutant distribution and toxicity.This work proposes a main framework of and SDI for monitoring the dynamic activity of endocrine disrupting chemicals in water. The proposed SDI is based on multiple remote sensing stations equipped by a set of impedentiometric immunobiosensors coated with ER-α receptor on an ArduinoMEGA® microcontroller-board.The remote sensings are designed to gather spatial and temporal information on the type and the concentration of different EDCs compound in the sampled water.The remote sensing stations are also fitted to communicate the measured data by GPS to a central server-side, thanks to the ArduinoGSMShield®. On the server side a QSAR model is installed to estimate EDCs activity, on the basis of 2 datasets on On this view, the proposed SDI represents a useful tool to support decision-makers on regulatory policies that are inclusive of monitoring strategies.

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“…Bitella et al (2014) designed a novel, low-cost hardware platform that incorporates sensors for recording air temperature and relative humidity as well as soil temperature and moisture content at multiple depths. Given the low cost of these sensors, they could be spaced at close, regular intervals throughout the field, providing a high-resolution sampling grid.…”

Section: Envirotypingmentioning

confidence: 99%

The quest for understanding phenotypic variation via integrated approaches in the field environment

et al. 2016

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A Novel Low-Cost Open-Hardware Platform for Monitoring Soil Water Content and Multiple Soil-Air-Vegetation Parameters

Cited by 85 publications

References 53 publications

Developing a Hydrologic Monitoring Network in Data‐Scarce Regions Using Open‐Source Arduino Dataloggers

Developing a Hydrologic Monitoring Network in Data‐Scarce Regions Using Open‐Source Arduino Dataloggers

A biosensored spatial data infrastructure for the dynamic monitoring of the presence and the activity of endocrine disrupting chemicals in water

The quest for understanding phenotypic variation via integrated approaches in the field environment

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