NEW DELHI: Indian scientists have developed a sensor-based ‘Electronic Nose’ for sniffing out variety of gases at pulp and paper mill industries and environmental monitoring at other sensitive locations.
The gases, emitted by these industries beyond certain concentration, may adversely affect human health and environment.
This sophisticated portable device can measure odour concentration and odour intensity and thereby can immediately alert workers in such industrial units for remedial action.
Though the ‘Electronic Nose’ is currently being successfully used in couple of paper mills in Karnataka and Tamil Nadu, the researchers are also working on its application to monitor gas emissions from any source, be it an industry or leakage of petroleum pipes going through fields or farms.
The devices is developed by the Nagpur-based National Environmental Engineering Research Institute (NEERI) of the Council of Scientific and Industrial Research (CSIR) and the Centre for Development of Advanced Computing (C-DAC) of the Department of Electronics and Information Technology of the Government of India.
“This has been the first attempt in India to develop such a product using odour sensors that make use of intelligent software to identify odorous molecules. It is also possible to train the software by feeding information based on observation of experts”, said a statement, issued by the ministry of science and technology on Wednesday night.
The pulp and paper industry emits a variety of gases, namely, hydrogen sulphide, methyl mercaptan, dimethyl sulphide, and dimethyl disulphide. These gases beyond a certain concentration may adversely affect the environment and human health.
“This newly developed ‘Electronic Nose’ helps in continuous monitoring of these gases, overcoming all limitations of the available analytical instruments that are not only expensive and time-consuming. The Electronic Nose can easily be operated at a pulp and paper mill industry”, said the ministry.
The ‘Electronic Nose’ uses an array of sensors that function on the principle similar to that of human olfaction. The sensor array generates a pattern based on the type of aroma. The patterns obtained are trained to help interpret and distinguish amongst various odors and odorants as well as to recognize new patterns using advanced mathematical techniques, such as pattern recognition algorithms, principal component analysis, discriminant function analysis, cluster analysis, and artificial neural networks.