{"title":"Automated control system design for Ultra Supercritical thermal power plant","authors":"P. Kiruthika, P. Navaseelan, L. Senthilnathan","doi":"10.1109/TIAR.2015.7358554","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358554","url":null,"abstract":"The work taken up for this paper is the implementation of process automation using DCS for Ultra Supercritical thermal power plant. The control of large scale ultra super critical power plant is very complicated and highly non linear because it involves the measurement and control of number of parameters in order to increase the overall plant efficiency by Optimizing the combustion process, increasing the steam parameters, reducing the condenser pressure and improving the internal efficiency of the steam turbines. Thus, Monitoring and control system such as DCS/SCADA are responsible for managing critical infrastructures operating in these environment. The control of various components such as once through boiler parts super heater (temperature, pressure, flow), reheater (temperature, pressure, flow), economiser (temperature, pressure and flow), air Preheater (temperature), burners (air/fuel ratio) and turbine operating conditions is implemented using the CENTUM CS 3000 of Yokogawa India ltd.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132128539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Providing Smart Agricultural solutions to farmers for better yielding using IoT","authors":"M. Gayatri, J. Jayasakthi, G. S. Anandha Mala","doi":"10.1109/TIAR.2015.7358528","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358528","url":null,"abstract":"The field of Cloud computing is helping in leaps and bounds to improvise our age old business - Agriculture. Practical applications can be built from the economic consumption of cloud computing devices that can create a whole computing ecosystem, from sensors to tools that observe data from agricultural field images and from human actors on the ground and accurately feed the data into repositories along with their location as GPS co-ordinates. In reality, sensors are now able to detect the position of water sources in a subject that is being investigated. Issues related to farmers are always hampering the course of our evolution. One of the answer to these types of problems is to help the farmers using modernization techniques. This paper proposes an approach combining the advantages of the major characteristics of emerging technologies such as Internet of Things(IoT) and Web Services in order to construct an efficient approach to handle the enormous data involved in agrarian output. The approach uses the combination of IoT and cloud computing that promotes the fast development of agricultural modernization and helps to realize smart solution for agriculture and efficiently solve the issues related to farmers.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116631001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Chawla, Nitasha Hasteer, Prashant Kumar, C. Ghanshyam, Manisha Singh
{"title":"Prediction of pollution potential of Indian rivers using empirical equation consisting of water quality parameters","authors":"P. Chawla, Nitasha Hasteer, Prashant Kumar, C. Ghanshyam, Manisha Singh","doi":"10.1109/TIAR.2015.7358560","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358560","url":null,"abstract":"Over the years the surface water quality of Indian rivers has been degrading. There are various reasons for the degradation of quality of river waters in Indian conditions. The pollution potential of river water involves various factors such as pH, Conductivity, Dissolved Oxygen, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Coliform and Fecal Coliform. The paper presents an approach to develop an empirical equation to predict the pollution potential of river water. The empirical equation developed uses aforementioned factors as variables. These variables have been assigned various ratings on a scale of 1-3 according to standard pollution potential charts. The pollution potential predicted using this empirical equation is in congruence with the current potential pollution of Indian rivers.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122654434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Software sensor for potable water quality through qualitative and quantitative analysis using artificial intelligence","authors":"Nisarg Desai, L. D. Dhinesh Babu","doi":"10.1109/TIAR.2015.7358559","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358559","url":null,"abstract":"The analysis and control of potable water quality is increasingly fascinating due to its impacts on human life. Numerous lab-scale and field-scale treatment and sensing methods are created in this field to safeguard this natural vital asset. From long several methods were experimented determining water quality including traditional one's such as wet-chemistry which needs reagents, electro-chemical based, and most recently machine learning based software models to name a few however, performance enhancement and development of truly ion-selective electrodes has been still area of most interest and current area of research world-wide. In this paper, spectroscopic fusion for quantitative determination of qualitative attributes of water parameters will be explored with the application of chemometrics. An integration of multi-spectral, surface enhanced Raman spectroscopy, UV-Visible spectroscopy in the presence of multi-sample holder made off with and without nanostructured substrate will be attempted, and the patterns would be analyzed using Principal Component Analysis and other similar Machine Learning techniques. A set of pseudo-sampling matrix comprising of training and validation sets would be demonstrated on a lab-scale basis as a proof-of-concept. This paper also aims to overview existing practices, and presents proposed approach which would be free from reagent, rugged, and field-usable method, and would use fusion of spectroscopy, nano-structured sample holder, and Machine learning extraction algorithms.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117110657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A case study on VoIP over WMN based architecture for future e-governance of Indian rural areas","authors":"B. Loyd, D. Sivakumar","doi":"10.1109/TIAR.2015.7358533","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358533","url":null,"abstract":"National e-Governance Plan (NeGP) targets to provide all government services to the common man in his own locality, through state wide area networks SWAN. Latest survey shows that operators are not conducive to cover rural areas of India as the customer density is lower and they spend lesser on phone calls. For the efficient e-governance of Government of India, this paper puts forth a case study on VoIP over Wireless Mesh Networks in order to extend the low cost communications to the Indian rural areas. VoIP over Wireless Mesh Networks would be a potential solution to connect the digitally cornered rural areas of India. In this paper, we presented an exhaustive case study on test bed design for VoIP over Wireless Mesh Network that utilizes multiband IEEE 802.11 access points as mesh router nodes, Asterisk SIP server with Private Branch eXchange (PBX) and gateways with UTRAN interface in order to route phone calls and other services by not using any base stations or landlines. The study seeks details of WMN router node and mesh client node protocol stack, VoIP performance over WMN, hardware design, software design, integration with core network and PSTN and routing calls. The case study concludes that VoIP over WMN based architecture will provide the phenomenal platform to construct State Wide Area Networks (SWANs) for future e-governance of Indian rural areas.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132082916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Priya, C. Kumaravelu, A. Gopal, Pearley Stanley
{"title":"Classification of rice varieties using Near-Infra red Spectroscopy","authors":"B. Priya, C. Kumaravelu, A. Gopal, Pearley Stanley","doi":"10.1109/TIAR.2015.7358524","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358524","url":null,"abstract":"Rice is consumed in many different forms (brown, milled and parboiled) and cultivated in different size varieties (short, medium and long grain). Many of the traditional methods of analysis for determining the physical, chemical and mechanical properties to ensure the quality of rice are time consuming, destructive, require expensive harmful reagents. The desire is to replace the traditional methods to find its quality with rapid, non-destructive, non invasive methods. All cereal grains contain starch (soluble carbohydrate) as the principal component. Starch makes up about 90% of the dry matter content of milled rice. The objective of this study is to classify rice samples based on the carbohydrate content by using the Near-Infrared Spectroscopy (NIRs). NIR spectra were taken on every 250 gm of rice in the range of 1100nm to 2200nm. All the spectral data were processed statistically and resulting, the rice samples were classified using Principle Component Analysis (PCA).","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123826866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling, identification and detection of faults in industrial boiler(July2015)","authors":"Navaseelan Paul David, B. Swaminathan","doi":"10.1109/TIAR.2015.7358557","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358557","url":null,"abstract":"The Boiler plays vital role in electric power plants, fertilizer industries, petrochemical and in other industries. In such industries the boiler actuates turbines, compressors for generating electric power, pneumatic power respectively. The overall operation and efficiency of any plant is depending on the quality of steam produced in terms of its flow rate, pressure and temperature and also reliability. Any kind of fault or failure of the boiler may reduce the quality of production and tend to shut down the operation of entire plant. Hence early detection of faults will enhance availability of steam and reduce plant shutdown. In order to diagnose the faults, complete operation of all the loops like feed water circuit, air fuel circuit, steam circuit and cooling water circuit are studied and possible failures at the input side, inside the boiler and output side of the boiler are studied. One such 130 tons per hour capacity water tube boiler in Petrochemical industry is studied. The required data for complete transient part of its operation is collected for identification of the boiler model. In this paper simple models using first principle balance equations were developed for the subsystems of the boiler like furnace, boiler tubes and drums and heat exchangers. The mathematical models are also obtained based on measured data during real time operation of the boiler. Then the parameters are identified by choosing proper model structure like non-linear ARX and Hammerstein-Wiener and it is validated with real time plant data. The model based fault detection using Kalman filter algorithm is presented in this paper among the different methods being practiced. In this method, Kalman filter estimates all the process variables at the input side, output side and inside the boiler. Residual is generated as the difference between measured and estimated values of these variables. If the residual generated surpasses threshold value indicates fault in the boiler.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123191828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection and quantification of pathogenic bacteria using giant magnetic resistance sensor","authors":"S. Bharath, A. Sam, K. Kalaivani","doi":"10.1109/TIAR.2015.7358550","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358550","url":null,"abstract":"Clinical diagnosis of bacteria is very important. Currently there are many methods like ELISA (Enzyme Linked Immunosorbent Assay), PCR based method (Polymerase Chain Reaction), optical method and various other methods used for detecting the bacteria. ELISA and PCR based method takes more time for producing the results. The optical method suffers from the high background noise caused by stray light. Thus there is need for developing a device that is cheap and more sensitive. The magnetic sensing device is the best candidate to meet this criterion. Giant magnetic resistance (GMR) sensor is cheap, small and sensitive when compared to the other available magnetic sensors. Here the bacteria are tagged with Fe2O3 magnetic nano particles of size 40nm coated with suitable antibody. When external magnetic field is applied to the magnetic nano particles it will produce a local magnetic field and this magnetic field will cause change in the resistance of the GMR sensor. Thus by detecting the quantity of magnetic field produced by the magnetic nano particles the amount of bacteria in the sample can be quantified. The aim of the paper is to design a cost effective device that can sense the bacteria in the sample. Here the experimental setup has been designed and tested with different functionalized magnetic nano particles immobilized on the GMR sensing surface and applying the magnetic field in the z-axis direction.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129686875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparing prediction accuracy of OK and RK for the soils of Surat talukas","authors":"Jaishree Tailor, R. Gulati","doi":"10.1109/TIAR.2015.7358558","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358558","url":null,"abstract":"Prediction of soil properties plays a significant role in forecasting, assessment of risks as well as decision making for Government, agriculturist and other geoscience stakeholders. The acquisition process for these type of data is difficult, time consuming, and expensive. Geographical Information Systems uses several spatial interpolations like Splines, IDW, and Kriging etc. to predict or interpolate unknown environment variables. Kriging belongs to the category of geostatistical interpolation techniques. The major emphasis of this paper is on ordinary kriging which is a method based on weights and regression kriging which is a hybrid method of geo-statistics. This paper compares ordinary kriging that with regression kriging by testing soils of three talukas of Surat district namely Bardoli, Mandvi and Umarpada. Data related to soil major nutrients and micro nutrients have used for comparison. The prediction accuracy of regression kriging is almost 100% as compared to ordinary kriging in three cases taken as sample. Thus the paper signifies the use of kriging techniques for predicting soil properties for these three talukas of southern Gujarat.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130760110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and prototype implementation of indoor air quality monitoring using LonWorks technology","authors":"K. Yogalakshmi, R. Sudha, C. Selvam","doi":"10.1109/TIAR.2015.7358556","DOIUrl":"https://doi.org/10.1109/TIAR.2015.7358556","url":null,"abstract":"Environmental Protection Agency (EPA) shows indoor air is 2-3 times more polluted than the worst outside air. These pollutants also lead to simple asphyxiation as general health hazard which ensures the importance of indoor air quality (IAQ) monitoring. Therefore maintaining a good indoor air quality improves the health zone of the peoples both in urban and rural areas. Peoples in rural areas are more affected because burning woods and papers are common practices occurring since there is no much awareness about indoor pollution. Studying about indoor air pollutants is important in order to know about the health hazards caused, exposure limits and sources of the pollutants in the living place which makes a right path way to know about the presence and absence of particular pollutant. The proposed system comprises of low cost sintered metal oxide gas sensor which are general air contaminant sensors. These sensors can sense gas concentrations in ppm level which makes it suitable for the indoor air quality monitoring. Testing of the sensors is been carried out in microcontroller to study their real time characteristics. Later sensors are connected to the LonWorks module. LonWorks technology is a cost effective protocol for building automation system. This communication protocol ensures reliable and energy efficient solution to building automation system.","PeriodicalId":281784,"journal":{"name":"2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130522120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}