Major Thematic Area

Water resources and pollution treatment

Duration of the Project

8 years

Project partners details

Brazil Russia India China South Africa
Prof. Osvaldo Novais de Oliveira Jr,Physics and Material Science, University of Sao Paulo Dr. Andrey Legin Head of Laboratory of Artificial sensory systems,ITMO University St. Petersburg, Kronverkskiy Dr. Nabarun Bhattacharyya Director C-DAC,Kolkata India Dr.Ping Ping Wang, Director of Biosensors National Special Laboratory, Zhejiang University, Hangzhou, China Dr. Mark Laing, Director ACCI Room 228 Rabie Saunders Building Agriculture Campus Pietermaritzburg

Brazilian Partner

The Brazilian team will mainly contribute on the development of hybrid nanostructured sensors coupled to lab-on-a-chip devices. For producing the sensors, hybrid nanofilms and nanofibers of high surface area, composed by distinct nanomaterials in nature will be employed as sensing units in impedimetric e-tongue devices. Additionally, the use of the pencil’s graphite core as sensing units for impedance spectroscopy analyses will also be employed. The e-tongues will be coupled to microfluidics using polydimethylsiloxane (PDMS) and 3-D printing technology approaches, envisaging lab-on-a-chips devices for on-site analysis of water resources in a reliable and expedite way, using small amount of water samples.

Russian Partner

Russian research team will be mainly concentrated on the development of multisensor systems based on potentiometric sensors for express evaluation of important water quality parameters. For this purpose a variety of novel sensors and sensor arrays with high cross-sensitivity to the substances and integral features of interest (e.g. COD) in the water will be developed. Special attention will be also paid to multivariate data processing in order to establish mathematical procedures for sensor drift compensation, ensuring long term usage of predictive models relating sensor responses with water quality parameters. HPLC, capillary electrophoresis, ICP-MS and other conventional methods will be employed for validation of the suggested methodologies, especially with respect to selected organic compounds and certain inorganic components which may be present in water as potential toxic substance.

Indian Partner

Indian Partner: Our previous experience shows that it is possible to have an initial assessment of water quality by E-Nose and E-Tounge technology. However the analytical methods can take robust shape if we can integrate the sensing technologies and make them IOT compatible. We plan to * (i) make the existing IOT enabling of the proven sensing technologies * (ii)we will work out the right combination technology that be appropriate for enabling large scale detection * (iii) the algorithmic design that will enable simultaneous data-dialogue with cloud (which may be shared with the partner countries) will be undertaken as permissible by the laws existing in the partner nation. The technique will be employed in monitoring of local water bodies e.g. Ganges which flows from Himalaya to the Bay of Bengal. * How pollutants change water structure, dielectric properties and impedance and how to monitor them using optical and potentiometric sensors will be explored.

Chinese Partner

The Chinese team will mainly contribute on the development of the bionic electronic eye (Bionic e-Eye), which is a smartphone-based hand-held optical system and able to realize high-throughput, rapid and simultaneous detection of marine toxins, Bionic e-Eye was combined with ELISA to makes it suitable to realize the high-throughput, rapid and quantitative analysis on shellfish toxins. The cell viability sensor (CVBS) using living cells as sensing elements was combined with Bionic e-Eye to develop a novel rapid in-field analysis method for marine toxins. Two kinds of gold immunochromatography assay (GICA) strips will be used for hand-held fast detection of marine toxins often a measure of water quality and safety in shorelines. Combination technology will be used for detection of multiple target toxins. Large amount of sensing data on marine toxins towards will be used , that would act as water toxin big data and cab subjected to analysis by artificial intelligence.

South African Partner

The South African team will contribute to the development of the multimodal, water quality sensor systems. This will be performed * South African FISHTRAC study exists which satellite imaging is employed to track fish. * As fish trajectory largely depends and is affected by water quality the method can be indirectly employed to track water quality in deep sea * This will include the real-time monitoring and associated data management system experiences from South Africa. * The South African team will also contribute to the development of and testing of the data management system and associated cloud based database and interface system for the holistic management of environmental water quality through a case study in South Africa. * Real-time or near real-time water quality monitoring and management system at ±12 river sites on the Umgeni River in KwaZulu-Natal where existing FISHTRAC systems are being tested. Results from this case study will demonstrate the application of the environmental water quality monitoring system, its socio-ecological value and application in a real life case study. The approach adopted and outcomes of the South African case study will be written up as a collaborative output and learning experience for this study.

Common Goals

  • To generate new generation sensors that introduce novel ways of water monotoring. Emerging technologies like microfluidics,nanotechnology and 3D printing will be used to fabricate new devices.
  • To make the existing or newly introduced devices IOT and cloud compatible so that seamless interface with endusers say having smart phone can be made.
  • New biophysical location based mapping of water resources in presence and absence of pollutants using spectroscopic , dielectric and impedance based technques.
  • Integrating satelite based imaging data with local sensor data.
  • Generating bigdata for water in water bodies of National importance in respective BRICS counries.

Common Public Good

Since water analysis has a social impact that does need any mention it is hoped the outcome of teh project will have a significant social impact.