Sensorscope: Sensor Networks for Environmental Monitoring

What is Sensorscope?

   The natural environment is undergoing dramatic changes, yet all too often we cannot provide satisfactory answers to open questions, such as “how much change is anticipated?” or “what are the main causes and consequences of such change?”. A prominent example of such change is global warming, which strongly influences alpine ecosystem and hydrologic function as well as the formation of hazards from alpine peaks to valley bottoms. The primary limitation to address these socially relevant questions has been the essential lack of appropriate spatial and temporal environmental observations across the landscape in which environmental engineers and scientists can test and validate models which simulate future scenarios and make real-time predictions.

Wind fields in Genepi rock glacier

Until now, there have been only limited field campaigns with in-situ spatial observations. These campaigns have generally focused on deploying relatively few “expensive” sensing stations limiting the spatial coverage. The high cost of such systems makes it difficult for scientists to deploy a large number of sensing units. Furthermore, such instruments commonly use data loggers attached to the sensing devices to store their data. Such a storing technique suffers from limited capacity and does not allow the user to get an immediate feedback from the system. Indeed, one must physically go to each monitoring station in order to download their data. As a result, using or monitoring such a system can quickly become time consuming and tedious.

 

The SensorScope project addressed these issues by developing a large-scale distributed environmental measurement system centered on a wireless sensor network with a built-in capacity to produce high temporal and spatial density measures. This innovative system is composed of multiple solar-powered sensing stations which communicate wirelessly, constituting a sensor network. The sensing stations measured key environmental data such as air temperature and humidity, surface temperature, incoming solar radiation, wind speed and direction, precipitation, soil water content, and soil water suction. The design of the sensing stations was conceived with the following baseline requirements: low energy consumption, long communication range, low cost, simple installation, energy autonomy, high-quality data, water resistance and the prospect of retrieving data in real-time.

Sensorscope station in "Plain Morte" glacier

 

These sensing stations periodically sample their sensors and transmit their readings through the wireless network to a collection point (base-station). The base-station forwards this data to a central server and makes it available to the user in real time. SensorScope allows environmental scientists to use a comprehensive portal to survey, analyze and control the measurement process through a web-based interface. In addition, it is also possible to easily add/remove sensing stations, change the set of sensors of any particular sensing stations, or change the geographic location of the measurement points.

SensorScope provides low cost, wireless and reliable sensor network systems for environmental monitoring to a wide community. It improves present data collection techniques with the latest technology, while meeting the requirements from the environmental scientists.

 

Project contributions

  • Development of a new generation of measurement system based on a wireless sensor network with built-in capacity to produce high temporal and spatial density measures. 
  • Push the limits in real-time environmental measurement by deploying sensing stations in the Swiss Alps. 
  • Development of a complete communication stack well-fitted to harsh deployment sites (e.g., isolated places, harsh meteorological conditions) featuring multi-hop routing and synchronization among stations, as well as an advanced energy management of the radio chip.
  • Technology transferred to Sensorscope Sarl.

 Luce deployment at EPFL campus

Funding

What to know more?

   If you have any question about our work or Sensorscope in general, feel free to contact us at the following e-mail address:

guillermo [DOT] barrenetxea [AT] epfl [DOT] ch

Main Publications

C. Ranquet Bouleau; T. Baracchini; G. Barrenenetxea; A. Repetti; J.-C. Bolay : Low-cost wireless sensor networks for dryland irrigation agriculture in Burkina Faso; Technologies for Development. What is Essential?; Cham Heidelberg New York Dordrecht London: Springer International Publishing, 2015.
N. C. Ceperley; T. Mande; M. B. Parlange : Depletion of Stem Water of Sclerocarya birrea Agroforestry Tree Precedes Start of Rainy Season in West African Sudanian Zone ; European Geosciences Union, General Assembly 2013, Vienna, Austria, 07-12 April 2013.
W. C. Evans; A. Bahr; A. Martinoli : Distributed spatiotemporal suppression for environmental data collection in real-world sensor networks. 2013. 9th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), Cambridge, Massachusetts, USA, May 21-23, 2013. p. 70-79. DOI : 10.1109/DCOSS.2013.74.
P.-A. Abdelmoula : Measurement of Leaf Area Index for Calculation of Water Consumption by Agroforestry Trees in Burkina Faso ; 2012.
C. Wiedmann : Variability of Rainfall in a Semi-Arid Catchment in Burkina Faso ; 2012.
Y. Ruffieux; A. C. Davison : Hierarchical wavelet modelling of environmental sensor data; Brazilian Journal of Probability and Statistics. 2011. DOI : 10.1214/11-BJPS154.
N. Ceperley : Water use by Sclerocarya birrea Agroforestry Trees in Sudanian Savanna: Application of Wireless Sensor Networks ; European Geosciences Union (EGU) General Assembly, Vienna, Austria, April 8, 2011.
N. Ceperley : Evaporation over a Heterogeneous Mixed Savanna-Agricultural Catchment using a Distributed Wireless Sensor Network ; American Geosciences Union (AGU) General Assembly, San Francisco, USA, December 15, 2010.
R. Mage : Développement de méthodes de modélisation des flux turbulents dans un environnement alpin en utilisant des réseaux de stations micrométéorologiques ; 2010.