Inspired by Henry David Thoreau, an environmentalist, who spent a great part of his life examining natural bodies, Thoreau is an initiative to collect and share high resolution sensing data on water and soil.
Over a hundred and fifty years after late Henry David Thoreau, developments in sensor and wireless technologies, microelectronics, data science and the emergence of the cloud are making it increasingly feasible to collect vast amounts of environmental data at high spatial and temporal resolutions over large geographical areas. Monitoring the land and large water bodies in this unprecedented manner using sensor networks has the potential to deeply impact environmental science, soil and plant science, and agriculture. This in turn, impacts food security, human health, and ecology.
It is with this intent that the Guha group at the University of Chicago explores sensor networks, for water — to measure water pollution and its impact on human health in Indian rivers; and for soil, using a fully buried wireless subterranean sensor network on campus at the University of Chicago.
Our demonstration of the deployment of a large-scale, cloud-based, fully buried Wireless Underground Sensor Network (WUSN) with long, continuous operation time takes place in an agricultural site - specifically, a farm field - near Fermi National Laboratory. The Thoreau WUSN at the agricultural site consists of an above-ground Sigfox base station in the center of the field alongside 25 buried sensor nodes. Each sensor node collects soil data which is then relayed to the receiving antenna in a single hop. We estimate that this low-power IoT solution will operate on four AA batteries for just over four years.
In this Thoreau sensor network deployment, each node is buried between 14 and 15 inches below the surface, and broadcasts wirelessly from that position every thirty minutes. Each sensor contains a high-precision soil sensor, the Teros 12, which measures soil temperature (T), electrical conductivity (EC), and a raw sensor value that may be converted to dielectric permittivity (DP) or volumetric water content (VWC). These parameters, all related to soil water, will allow us to track and understand agricultural development in the field over the course of months and years in real time
This Thoreau deployment uses the Sigfox network in the unlicensed 902 MHz band using an ultra-narrow band transmission scheme. Packets are a maximum of 12 bytes long, and is allowed a bandwidth of 100 Hz with a transmission power of 22 dBm. To minimize power use, we select that each packet is transmitted precisely once per cycle (as opposed to three times, which is default) on a randomly chosen frequency within the 902 MHz band. Furthermore, the packets are sent asynchronously, and are not acknowledged or retransmitted. The data packets are received by the central base station planted in the field, then transmitted to the Sigfox cloud and our internal server for processing.
Water-to-Cloud is an initiative to map water quality over large water bodies using in-situ cyber-physical systems. We are on a mission to create a repository of reliable water quality data from rivers across India. We believe that putting out such comprehensive and actionable data in the public domain can lead to positive action to improve the health of our water bodies. This initiative is currently supported by Tata Center for Development at UChicago.
Our approach. We collect exponentially high number of data points in a limited time and space (say ~1000 data points in three hours over 10 square km of water body). This data is visualised into water quality maps that show spread of pollution across time and space. These thoreau maps, as we call them, are freely available for anyone who wants to learn about the quality of our surface waters.
We map river water quality by using mobile, time-stamped and geo-tagged cyber-physical sensors in the following manner:
• We attached sensors to a boat that goes on a pre-defined route;
• The sensor probe is immersed in water and handheld meter records the data;
• Then, the data is downloaded from sensors, cleaned, and uploaded onto this portal.
Using mobile sensors, we measure pH, dissolved oxygen, temperature, turbidity, electrical conductivity, colored dissolved organic matter, nitrate, ammonia and tryptophan fluorescence basis the availability of sensors. We also do point sampling for testing Bio-chemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), fecal coliform, total suspended solids, major ions and heavy metals through laboratory based analysis.
In India, almost 40 billion litres of sewage is generated every day with only a tiny fraction being adequately treated. As a result, a shocking 70% of surface waters are now polluted and not fit for consumption
. However, what cannot be measured cannot be fixed. There are significant gaps in the traditional approach to surface water quality monitoring
Lack of data points: Limited water samples collected once in one to three months;
Costly and lengthy process to measure water quality: Tedious process of sending water samples to labs for analysis;
Prone to manual mishandling: High probability of human error while collecting, transporting or analysing samples;
Limited scope of analysis: Hard to create visualizations with conventional datasets;
No open source platform: Whatever little data that exists is difficult to access and interpret. Water-to-Cloud offers an alternative to this traditional approach.
We are looking for a postdoctoral researcher candidate to carry out research on an NSF-funded project focusing on developing integrated silicon photonics-based sensors for point-of-interest soil micronutrient detection. View more details here.