In September 2018, Harriet Wilson, ESR for MANTEL Project 1, travelled to India to deploy weather & soil moisture sensors built using low-cost & open-source technology. The fieldwork was part of a wider project funded by the IUKWC, investigating the use of low-cost sensor technology for validating Earth Observation data.
Low-cost and open-source sensor technology offers huge gains for environmental monitoring. Long-term ecosystem monitoring and dense sensor networks are limited by high equipment and maintenance cost. Even with the advancement of available satellite and modelled data, ground observation data is still required for calibration and validation. This creates a huge spatial bias in environmental sciences, as the distribution and longevity of even the most important climate variables such as temperature and precipitation is highly variable across the globe (see Fig 1.).
Low-cost sensor technology can dramatically reduce the equipment cost of monitoring networks, and open-source technology facilitates trouble-shooting support from the user-community and reduces external maintenance costs. The potential with low-cost sensors is vast, including larger and denser sensor networks, lower (financial) risk experiments, and improving long-term monitoring for areas where data is lacking.
Microcontrollers (which are essentially a tiny computer, see; Arduino for a range of common designs) offers novice users an easy introduction to building sensor-based automated systems. Open-source hardware and software has been vital in advancing the science and bringing down the costs of parts (cloned parts are easily available). User development platforms such as Instructables & Arduino Playground facilitate the sharing of designs and support for users. Sensor system designs may be as diverse as the users, ranging from simple temperature sensors to text messaging plant monitoring schemes.
The sensors I deployed were based on the FreeStation Meso Automatic Weather Station and a soil moisture sensor designed by the King’s College London John B Thornes laboratory. The FreeStation records air temperature, precipitation, humidity, solar radiation, wind speed and wind direction. The FreeStation receives power from the solar panel on the roof, which is directed through a regulator and stored in rechargeable batteries for use during the night. The data will then be recorded on a SD card in an excel format for simple retrieval, but can also be communicated using WiFi or GSM. FreeStation users are then required to upload their data to contribute towards the FreeStation network of hydrological and ecosystem models. The soil moisture sensor also records hourly onto an SD card and is a compact, water-tight and low-power design, which can operate on 4 AA batteries for up to 4 months. The sensor can have multiple probes connected which can be buried at different depths. The material costs for these sensors is around; £110 for the FreeStation Meso, and around £25 for the soil moisture sensor.
For a project funded by IUKWC, I built two FreeStations Meso weather stations and soil moisture sensors which were deployed at the University of Delhi and the Banaras Hindu University in Varanasi. The aim of the fieldwork was to explore the use of low-cost sensors for validating satellite soil moisture products in India. Soil moisture is a particularly important variable for ‘hotspots’ for land-atmospheric coupling, such as India (see GLACE: Koster et al., 2006). Therefore, the integration of soil moisture satellite data into weather and climate models, could greatly improve weather prediction (particularly the Indian monsoon), with huge social and economic gains. However, findings from the project literature review and user survey, highlighted the lack of ground observation data as a key barrier to the uptake of soil moisture satellite data and satellite-derived modelled estimates. Low-cost soil moisture sensors could facilitate long-term soil moisture monitoring and also dense sensor networks for finer resolution studies with applications such as precision irrigation planning.
While low-cost & open-source sensors seem like a win-win for environmental monitoring, there are some inherent challenges which may need to be considered before opting for an open-source low-cost solution in new projects. One of the main considerations is the time-cost trade-off. While equipment costs are reduced, the initial time costs can be high. Sensors, even with instructions can take a long time to complete, especially for a novice in electronics. If building many sensors for a network, this design is quickly overcome, however it may not be such an obvious solution if building just one. Some sensors are, of course, simpler and easier to build than others, so starting small might pay off as a good idea. When paying very little for parts, faulty goods and longer lead times are more likely. If working to a tight deadline then you may have to counter in additional costs for buying parts from local and reliable manufacturers. Likely the best way to integrate low-cost & open-source sensor technology into environmental monitoring projects is step by step, such as in this project, starting with a small proof of concept study.
While the building and the sensor deployment was successful, the usefulness of these sensors will continue to be evaluated in terms of the data produced, the maintenance required and the assimilation of data into relevant monitoring practices. The fieldwork process highlighted some real-life applications for low-cost sensors, in terms of validating the use of EO products in India. Testing the sensors early on can help users to find appropriate end applications for the data, while feedback on the sensors can help develop sensor designs and network structures that match the requirements of these end users. In this project, collaborations have been formed with the universities visited in India, which are may feed into future projects.