Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697747
Rutuja Shinde, A. Thakare
Alzheimer disease is a brain disturbance disorder characterized by progressive dementia. The accurate diagnosis of Alzheimer disease plays important role in patients care. In some cases, it is difficult for a physician to analyse disorder at early stages. The Electroencephalography are useful tools to detect brain activities in normal and aged person to find abnormalities in the brain. The analysis of the EEG signals need to obtainefficient and effective methods to extract relevant information. The machine learning algorithms are efficient to predict Mild Cognitive Impairment (MCI) in patients. In this work, various EEG signal pattern studied in order to detect MCI. EEG data set is analysed and different classification algorithms are applied to the data set such as Linear Regression, Multi-layered perceptron, Sequential minimal optimization and Random forest.
{"title":"System and Method for Early Detection of Mild Cognitive Impairment","authors":"Rutuja Shinde, A. Thakare","doi":"10.1109/ICCUBEA.2018.8697747","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697747","url":null,"abstract":"Alzheimer disease is a brain disturbance disorder characterized by progressive dementia. The accurate diagnosis of Alzheimer disease plays important role in patients care. In some cases, it is difficult for a physician to analyse disorder at early stages. The Electroencephalography are useful tools to detect brain activities in normal and aged person to find abnormalities in the brain. The analysis of the EEG signals need to obtainefficient and effective methods to extract relevant information. The machine learning algorithms are efficient to predict Mild Cognitive Impairment (MCI) in patients. In this work, various EEG signal pattern studied in order to detect MCI. EEG data set is analysed and different classification algorithms are applied to the data set such as Linear Regression, Multi-layered perceptron, Sequential minimal optimization and Random forest.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130082245","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697784
S. Shinde, Sudeep D. Thepade
Face recognition is widely used in many applications and has been researched a lot since decades. Face recognition in combination with gender classification is the need for today's world. Gender classification has many specifications which have to be understood and calculated. This paper has proposed a system that can perform gender classification in most reliable, efficient and robust way. The technique is combination of image processing algorithm and data mining methodologies. The system applies the standard steps of image processing such as acquisition, pre-processing, feature extraction using LBG vector quantization method, the extracted features are passed to the data mining algorithms like Naïve Bayes, SVM Poly Kernel, SVM RDF Kernel and KNN for classification. Classification results are obtained for above classification techniques and analysis is performed on these results.
{"title":"Gender Classification from Face Images Using LBG Vector Quantization with Data Mining Algorithms","authors":"S. Shinde, Sudeep D. Thepade","doi":"10.1109/ICCUBEA.2018.8697784","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697784","url":null,"abstract":"Face recognition is widely used in many applications and has been researched a lot since decades. Face recognition in combination with gender classification is the need for today's world. Gender classification has many specifications which have to be understood and calculated. This paper has proposed a system that can perform gender classification in most reliable, efficient and robust way. The technique is combination of image processing algorithm and data mining methodologies. The system applies the standard steps of image processing such as acquisition, pre-processing, feature extraction using LBG vector quantization method, the extracted features are passed to the data mining algorithms like Naïve Bayes, SVM Poly Kernel, SVM RDF Kernel and KNN for classification. Classification results are obtained for above classification techniques and analysis is performed on these results.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134116585","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697467
S. Dicholkar, V. Dongre
Every Telecom Operator is concerned about availability of Microwave link as they are including availability guarantee of 99.999% in SLA. While achieving availability of 99.999%, installation cost is another major factor in consideration due to severe market competition. Three critical microwave links for availability improvement in plain terrain, hilly terrain and water bodies were considered for observation. First traditional techniques of availability improvement such as space diversity, frequency diversity were tried out but these techniques neither gave expected results nor saved cost. Finally new feature of IP radio i.e. adaptive modulation was used to achieve desired availability of 99.999% without increasing installation cost. Adaptive modulation is responsible for improvement in effective fade margin caused availability improvement of microwave link.
{"title":"Cost Effective Adaptive Modulation for Microwave Link Availability Improvement in Plain, Hilly Terrain, Water Bodies","authors":"S. Dicholkar, V. Dongre","doi":"10.1109/ICCUBEA.2018.8697467","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697467","url":null,"abstract":"Every Telecom Operator is concerned about availability of Microwave link as they are including availability guarantee of 99.999% in SLA. While achieving availability of 99.999%, installation cost is another major factor in consideration due to severe market competition. Three critical microwave links for availability improvement in plain terrain, hilly terrain and water bodies were considered for observation. First traditional techniques of availability improvement such as space diversity, frequency diversity were tried out but these techniques neither gave expected results nor saved cost. Finally new feature of IP radio i.e. adaptive modulation was used to achieve desired availability of 99.999% without increasing installation cost. Adaptive modulation is responsible for improvement in effective fade margin caused availability improvement of microwave link.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134411110","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697493
A. Kulkarni, S. S. Karandikar, P. A. Bamhore, S. Gawade, D. Medhane
Computers have become an integral part of the scientific world. The real-life problems are dealt with an algorithmic approach. Algorithms being independent of programming language, they can be developed using any natural spoken language that a person is comfortable with. However, the problem lies in implementing it. The computational intelligence model proposed in this paper approaches such problem by carrying out mapping at Semantic level using Natural Language Processing and ontology and applying Ontology Matching techniques to derive an automatic translator of natural language problem statement into the artificial language (here Java). The intermediate steps of translation are processed by using corpus of English for developing some techniques for mapping linguistic constructs to programming structures. The modern NLP techniques can make possible the conversion of natural language statements to a programming language. Overall, this paper proposes a knowledge-based expert system which makes use of facts and rules to build the solution.
{"title":"Computational Intelligence Model for Code Generation from Natural Language Problem Statement","authors":"A. Kulkarni, S. S. Karandikar, P. A. Bamhore, S. Gawade, D. Medhane","doi":"10.1109/ICCUBEA.2018.8697493","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697493","url":null,"abstract":"Computers have become an integral part of the scientific world. The real-life problems are dealt with an algorithmic approach. Algorithms being independent of programming language, they can be developed using any natural spoken language that a person is comfortable with. However, the problem lies in implementing it. The computational intelligence model proposed in this paper approaches such problem by carrying out mapping at Semantic level using Natural Language Processing and ontology and applying Ontology Matching techniques to derive an automatic translator of natural language problem statement into the artificial language (here Java). The intermediate steps of translation are processed by using corpus of English for developing some techniques for mapping linguistic constructs to programming structures. The modern NLP techniques can make possible the conversion of natural language statements to a programming language. Overall, this paper proposes a knowledge-based expert system which makes use of facts and rules to build the solution.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134088173","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}
Wireless Communication has established itself as an efficient and reliable medium for data transfer. But with the number of end users increasing exponentially and the availability of radio spectrum diminishing at a fast pace there is a need of an alternate approach for data transfer. The optical wireless communication proves to be an efficient alternate solution to solve the radio frequency spectrum crisis and also to overcome the constraints of the Wireless-Fidelity (Wi-Fi) technology. The LEDs used in our daily lives for the purpose of providing light when integrated with Li-Fi technology can make an efficient communication network for data transfer. This paper proposes cost-effective and working application of the Li-Fi technology to overcome the constraints of the existing data transmission technologies and to provide an alternate data transmission medium which is built on the existing infrastructure.
{"title":"A New Approach to Wireless Data Transmission Using Visible Light","authors":"Deepali Javale, Chinmay Atul Sashittal, S. Wakchaure, Ameya Phadnis, Sahil Santosh Patil, Rohan Sanjay Shahane","doi":"10.1109/ICCUBEA.2018.8697409","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697409","url":null,"abstract":"Wireless Communication has established itself as an efficient and reliable medium for data transfer. But with the number of end users increasing exponentially and the availability of radio spectrum diminishing at a fast pace there is a need of an alternate approach for data transfer. The optical wireless communication proves to be an efficient alternate solution to solve the radio frequency spectrum crisis and also to overcome the constraints of the Wireless-Fidelity (Wi-Fi) technology. The LEDs used in our daily lives for the purpose of providing light when integrated with Li-Fi technology can make an efficient communication network for data transfer. This paper proposes cost-effective and working application of the Li-Fi technology to overcome the constraints of the existing data transmission technologies and to provide an alternate data transmission medium which is built on the existing infrastructure.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130881304","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697724
Ashutosh Kale, Omkaar Khanvilkar, Hardik D. Jivani, Prathamesh Kumkar, Ishan Madan, T. Sarode
The objective of this research is to predict the next day's opening value of Nifty-100 index of the National Stock Exchange (NSE) using Artificial Neural Networks (ANNs). The ANN is trained using Error Backpropagation Training Algorithm (EBPTA). The multilayer feedforward network is trained using the present day's closing values of seven input parameters which are Gold, Silver, Copper, Crude Oil, Natural Gas and Foreign Exchange (FOREX) rates. In addition to these six rates, the closing value of Nifty-100 index was incorporated as input using Simple Moving Average (SMA) model. The relationship between each input parameter and Nifty-100 index was studied and analyzed using correlation technique. This research proves that Nifty-100 index can be predicted using ANNs.
{"title":"Forecasting Indian Stock Market Using Artificial Neural Networks","authors":"Ashutosh Kale, Omkaar Khanvilkar, Hardik D. Jivani, Prathamesh Kumkar, Ishan Madan, T. Sarode","doi":"10.1109/ICCUBEA.2018.8697724","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697724","url":null,"abstract":"The objective of this research is to predict the next day's opening value of Nifty-100 index of the National Stock Exchange (NSE) using Artificial Neural Networks (ANNs). The ANN is trained using Error Backpropagation Training Algorithm (EBPTA). The multilayer feedforward network is trained using the present day's closing values of seven input parameters which are Gold, Silver, Copper, Crude Oil, Natural Gas and Foreign Exchange (FOREX) rates. In addition to these six rates, the closing value of Nifty-100 index was incorporated as input using Simple Moving Average (SMA) model. The relationship between each input parameter and Nifty-100 index was studied and analyzed using correlation technique. This research proves that Nifty-100 index can be predicted using ANNs.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132818092","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697523
Snehal R. Kharvatkar, M. Sharma, D. Khairnar, Indraneel C. Naik
The pitch detection is an integral element of automatic music transcription system. Empirical Mode Decomposition (EMD) technique plays a key part in the pitch detection. With this technique, any complicated data set comprising of frequency-amplitude points can be decomposed into small number of finite Intrinsic Mode Functions (IMF). The IMF logic is in accordance with a well-behaved and well proven Hilbert transform. In this paper, a step by step algorithm for detecting pitch period from classical music signal based on Hilbert-Huang transform (HHT) is proposed. Traditional windowing methods have two limitations namely overlapping of windows and an assumption of stationary pitch period within a window. In contrast, HHT shows no limitations on window selection and allows pitch period changing within windows. It also can be used to monitor the variation of the pitch. To validate the proposed method, the pure tone of standard pitch is used. The results show that the variation of the pitch period can be accurately detected. This demonstrates the successful application of Hilbert-Huang transform for pitch detection from Indian classical music signal.
{"title":"Detection of Pitch Frequency of Indian Classical Music Based on Hilbert-Huang Transform for Automatic Note Transcription","authors":"Snehal R. Kharvatkar, M. Sharma, D. Khairnar, Indraneel C. Naik","doi":"10.1109/ICCUBEA.2018.8697523","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697523","url":null,"abstract":"The pitch detection is an integral element of automatic music transcription system. Empirical Mode Decomposition (EMD) technique plays a key part in the pitch detection. With this technique, any complicated data set comprising of frequency-amplitude points can be decomposed into small number of finite Intrinsic Mode Functions (IMF). The IMF logic is in accordance with a well-behaved and well proven Hilbert transform. In this paper, a step by step algorithm for detecting pitch period from classical music signal based on Hilbert-Huang transform (HHT) is proposed. Traditional windowing methods have two limitations namely overlapping of windows and an assumption of stationary pitch period within a window. In contrast, HHT shows no limitations on window selection and allows pitch period changing within windows. It also can be used to monitor the variation of the pitch. To validate the proposed method, the pure tone of standard pitch is used. The results show that the variation of the pitch period can be accurately detected. This demonstrates the successful application of Hilbert-Huang transform for pitch detection from Indian classical music signal.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133572269","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697685
Amol V. Dhumane, Shweta Guja, Sneha Deo, R. Prasad
Routing is a multifaceted process. Due to rapid changes in the current internet, it is possible to connect many smaller, bigger devices related to various applications to the internet. These devices are wired or wireless with sufficient or constrained resources. When these devices sense the data and transmit the data to the base station for analysis purpose, it becomes essential to understand the context of dynamic network for making the routing task easy. Here, context is considered as any information that can be used to understand the situation of the surrounding environment where we are running the application. Better routing mechanisms can be employed on the network when the application is aware with the context of the network. This generates the need of understanding the context of the network while routing the data. This paper mainly focuses on the context awareness and its need while routing the data and also discusses the context storage methods and context gathering phases.
{"title":"Context Awareness in IoT Routing","authors":"Amol V. Dhumane, Shweta Guja, Sneha Deo, R. Prasad","doi":"10.1109/ICCUBEA.2018.8697685","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697685","url":null,"abstract":"Routing is a multifaceted process. Due to rapid changes in the current internet, it is possible to connect many smaller, bigger devices related to various applications to the internet. These devices are wired or wireless with sufficient or constrained resources. When these devices sense the data and transmit the data to the base station for analysis purpose, it becomes essential to understand the context of dynamic network for making the routing task easy. Here, context is considered as any information that can be used to understand the situation of the surrounding environment where we are running the application. Better routing mechanisms can be employed on the network when the application is aware with the context of the network. This generates the need of understanding the context of the network while routing the data. This paper mainly focuses on the context awareness and its need while routing the data and also discusses the context storage methods and context gathering phases.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133192599","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}
This proposed technique of Adaptive learning dynamically adjusts the difficulty level or types of instruction based on individual student quality or preferences, and help to improve or accelerate a student's performance by providing instruction base on individuals. It addresses common teaching learning challenges, which includes student motivation, diverse student backgrounds, and resource limitations. Targeting instruction to the abilities and content needs of the individual student can reduce course drop-out rates; improve student outcomes and/or speed of achieving those outcomes, and enable faculty to dedicate their attention where it is most needed [3] The design and formation of the test depends on the questions. The test should cover all different levels of questions to make it more competitive. The main focus of this research work is assigning weightage to questions in the quiz based on the difficulty level. Assigning the weightage to question is a tedious task. This paper aims to discuss two methods for assigning weightage to the questions in the test and decide the difficulty level of the question [1].
{"title":"Adaptive and Automated Assessment System to Decide the Difficulty Level of Questions","authors":"Sunayana V Jadhav, Pravesh Jain, Yash Bhansali, Shwet Jain, Dishank Jain","doi":"10.1109/ICCUBEA.2018.8697433","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697433","url":null,"abstract":"This proposed technique of Adaptive learning dynamically adjusts the difficulty level or types of instruction based on individual student quality or preferences, and help to improve or accelerate a student's performance by providing instruction base on individuals. It addresses common teaching learning challenges, which includes student motivation, diverse student backgrounds, and resource limitations. Targeting instruction to the abilities and content needs of the individual student can reduce course drop-out rates; improve student outcomes and/or speed of achieving those outcomes, and enable faculty to dedicate their attention where it is most needed [3] The design and formation of the test depends on the questions. The test should cover all different levels of questions to make it more competitive. The main focus of this research work is assigning weightage to questions in the quiz based on the difficulty level. Assigning the weightage to question is a tedious task. This paper aims to discuss two methods for assigning weightage to the questions in the test and decide the difficulty level of the question [1].","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128897534","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}
Pub Date : 2018-08-01DOI: 10.1109/ICCUBEA.2018.8697520
Karuna. S. Lone, S. Chavan
This paper presents the conscientious system in order to make it fully Automated, ceaseless, cost and power effective system. The advanced technologies like wireless smart Intelligent network and Artificial Intelligence being implemented here with the help of Smart algorithms written in microcontroller. Here we have designed and implemented wind speed and direction sensor to provide the real time data gathering from the various nodes and keep track of all child nodes ceaselessly. In this way, the weather parameters like Temperature, Humidity, Wind speed and Wind Directions gets monitored ceaselessly and the faulty nodes can be detected very easily and such sensed data would be directly monitored by the maintenance team for further repairing of the faulty nodes by monitoring the data on the web page.
{"title":"Design and Implementation of Wireless Smart Intelligent Network System Using Artificial Intelligence for Monitoring Various Weather Parameters","authors":"Karuna. S. Lone, S. Chavan","doi":"10.1109/ICCUBEA.2018.8697520","DOIUrl":"https://doi.org/10.1109/ICCUBEA.2018.8697520","url":null,"abstract":"This paper presents the conscientious system in order to make it fully Automated, ceaseless, cost and power effective system. The advanced technologies like wireless smart Intelligent network and Artificial Intelligence being implemented here with the help of Smart algorithms written in microcontroller. Here we have designed and implemented wind speed and direction sensor to provide the real time data gathering from the various nodes and keep track of all child nodes ceaselessly. In this way, the weather parameters like Temperature, Humidity, Wind speed and Wind Directions gets monitored ceaselessly and the faulty nodes can be detected very easily and such sensed data would be directly monitored by the maintenance team for further repairing of the faulty nodes by monitoring the data on the web page.","PeriodicalId":422920,"journal":{"name":"2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637374","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}
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