The Internet of Things(IoT) represents a vision in which the Internet extends into a real world embracing everyday objects. The Physical items are no longer disconnected from the virtual world, but they can be controlled remotely and also serve as physical access points to Internet services. An Internet of Things makes computing truly ubiquitous and the early expectations of any new technology almost always surpass what is really achievable. Moreover, IoT has hit an inflection point in the minds of business executives across the globe. The very high level research challenges might be “IoT design”, but this includes a number of lower level research challenges such as Architecture, Interoperability and Scalability, M2M communication, Security, Connectivity, Compatibility , Longevity and Intelligent Analysis. IoT educate and train the students to develop Smart Cities, Smart homes, Smart Cars making use of the latest upcoming technologies.
The advancements in digital technologies had led to the abundance of Image datasets, various Image processing techniques to understand and deal with complex problems and challenges in adverse conditions in the image acquisition process, occlusion, objects with complicate shapes, with topological variations or undergoing complex motions. Computer Vision harnesses the power of complex Image Processing techniques to extract meaningful features from a given image or video samples. The students are continuously motivated which opens various avenues to do research in the fields like Medical imaging, Steganography, Video Surveillance, Forensic Analysis and Social Network analysis.
With the emergence of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. Machine learning techniques will be helpful to get insight, patterns and for better strategic decision making. Machine Learning deals with Pattern Recognition and Computational Learning in AI systems using sophisticated data-prediction algorithms and Artificial Neural Networks . The combination of Machine Learning algorithms is found in various applications like Face recognition, Gesture recognition, Fraud detection, Motion Sensing using Camera, Pattern recognition and Security Footage. The students are encouraged to focus their research in current emerging trends like robotics, Internet of Things, Big Data and deep learning
As worldwide systems extend the interconnection of universal information network, the smooth activity of communication and computing arrangements becomes vital. However, repeating attacks as virus and worm assaults and the achievement of criminal assailants delineate the shortcoming in current data advances and the need to give increased security in the network. Network security issue for the most part incorporates and organize network and information security. In particular, it alludes to the unwavering quality of system framework, classification, uprightness and accessibility of information data in the network. With this, the students are motivated in research, presents the system and network security advancements principally in detail, including verification, information encryption innovation, firewall innovation, interruption discovery framework , antivirus innovation and virtual private system. System security issue is identified with each system client, so the students must put a high incentive upon arranging security assaults and guarantee that the entire system is secured.
Big Data refers to all the data that is being generated across the globe at an unprecedented rate. This data could be either structured or unstructured. The tools used to store and analyze Big Data are Hadoop, Hive, HBase, Sqoop, Pig etc. The aspirants will focus on the Big Data applications in making digital India implemented in various sectors both public and private through activities like call logs, mobile banking transactions, online user generated content like blog posts and Tweets, online searches, satellite images into actionable information which require computational techniques to unveil trends and patterns within and between these extremely large socioeconomic datasets.
Cloud Computing has provided Big Data with a way to store and retrieve massive amount of information. It has evolved from personal cloud storage to entire organizations moving all of their data to the cloud. In the research market, cloud simulators are widely used by research scholars without paying fees to any cloud service provider. Using cloud simulators, researchers can execute their algorithmic approaches on a software-based library and can get the results for different parameters including energy optimization, security, integrity, confidentiality, bandwidth, power and many others. The students will focus and make some cloud computing models for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Robots are becoming an important fixture in our day-to-day life and also becoming a revolutionary based on innovative technologies. It is a platform in which the students are engaged in ground-breaking work in mechanism design, sensors, computer vision, robot learning, Bayesian state estimation, control theory, numerical optimization, biomechanics, neural control of movement, computational neuroscience, brain-machine interfaces, natural language instruction and physics-based animation. The students will currently focus to define large-scale joint initiatives that will enable us to leverage our multi-disciplinary expertise to attack the most challenging problems with the help of robotic automation in real world.
Student Name : Manjupriya. V
Domain : Networking
Co-ordinator Name : Prof.Dr.M.Rajendiran
Student Name : Pavithra. P
Domain : Cloud Computing
Co-ordinator Name : Prof.Dr.S.Malathi
Student Name : Sowmiya. S
Domain : Robotics
Co-ordinator Name : Prof.Dr.K.Valarmathi
Student Name : Ramya. S
Domain : Security
Co-ordinator Name : Prof.Dr.V.D.Ambeth Kumar
Student Name : Saranya. G
Domain : Internet of Things
Co-ordinator Name : Prof.Dr.V.D.Ambeth Kumar
A multitude of digital images preserve important data and so providing authentication to these images is often a challenging task. Although a number of image encryption techniques have been proposed, there are no encryption techniques capable of providing a noiseless mosaic image that does not require a large database. Thus, we propose a novel technique that transforms a secret image into a meaningful mosaic image of the same size that looks exactly like the preselected target image. The transformation process is handled by a secret key and only with that key a person can recover the secret image in alossless manner from the mosaic image. Hence,the secret fragment mosaic image creation technique is aimed to design a novel method that can, not only transform a secret image into a secret fragment-visible mosaic image of the same size, but also has the visual appearance of any freely selected target image, without the need of an actual database nor any compression techniques. Therefore, thisaids in preserving the crucial image data in a secure and safe manner.
Pleural effusion is the excess fluid within the pleural space. Pleural effusion detection helps in the diagnosis of diseases. If the effluent is not within the safe zone then it creates many problems including the death of human. The pleural level can be detected manually which is time consuming. The objective of this study is to determine the pleural fluid on computed tomography (CT) scan images automatically. The pleural space is segmented by parietal pleura extraction and visceral pleura extraction. The method is based on nonlinear anisotropic diffusion filtering and hybrid segmentation. 3D deformable modeling is applied for three dimensional view of the pleural effusion. We compare this method to manual segmentations and result is closer as expected. This method is useful in diagnosis of pleural effusion effectively rather than manual determination.
Software Testing is a formal process of checking whether a system or a product complies with the consumers need and requirement. It is mainly done by a dedicated testing team using different tools and techniques and the main intention is to identify deviations in the software product and to ensure quality. Testing is generally not done fully, instead it focuses on testing different test stages like Unit, Integration, System, User Acceptance etc., Testing also confirms with a product performance before launching it to the real world. It mainly prevents product failure or breakdown in large scale. The main goal of testing is to access the quality of the end product delivered to the customer. Testing life cycle focuses on different phases – Test plan, Test design, Test execution, Defect reporting and tracking it to closure etc., designing test cases based on requirements are the main building blocks of testing. This work is primarily focused during the test design stage of development. To write effective test cases in shorter time which identifies maximum defects is very crucial in testing life cycle. Effective test case sequencing or prioritizing the test cases based on criticality and risks is a key task of a tester. This methodology is to increase the fault detection at the earlier stage in testing. This prioritization technique organizes the test cases in sequential order in either ascending or descending order. This paper mainly focuses on effecting test sequencing identifying the right modules for testing during the planning phase and prioritize the same using OATS technique and application dependency structure algorithms
This paper shows a review on the offered methods for segmentation of brain tumor magnetic resonance imaging (MRI) and computed tomography (CT) images. Segmentation of brain MRI and CT images are broadly used as a preprocessing, for research that inhabit study and mechanization, in the domain of medical image processing. MRI and CT images segmentation is difficult job because of the same characteristics between hard and soft group of muscle anatomy in the brain image. Also the many parts of identical space present in an image differentiate with the image partition and direction. The selection of an suitable type for segmentation that is build up on the image featue. This review has been done in the point of view of authorize the mixture of a segmentation type for MRI and CT images. This review is differentiated based on the methods processed in segmentation.
Everyday new reports and stories started regarding innovations in Artificial Intelligence (AI) that comprise the probable to alter our lives. Navigation is a fundamental requirement of every individual. Visually impaired people require constant assistance for navigating from one location to another. Obstacle detection becomes a crucial point while dealing with people with visual impairments. Our intention is to build a mechanical framework to help outwardly hindered people explore gathering and enhance the standard of their life. The fundamental point of the planned agenda is to grow the electronic travel help for the visually impair and outwardly hindered people by developing into the ultrasonic innovation. Dazzle people (visually impaired) handle assortment of visual difficulties every day. In this paper, we proposed an inventive undertaking plan and usage of a Ultrasonic Navigation framework to furnish completely programmed deterrent location with capable of being heard warning for dazzle people. This visually impaired direction framework is sheltered, fearless and productive.
In recent years, Wireless device networks have achieved associate degree attention on a world level. This comprises small sensors with restricted power and restricted resources. The applicability of wireless sensor networks (WSNs) in various fields such as medical research and civilian applications is proliferating enormously. Every routing protocol designed for WSNs should be energy-efficient, reliable and prolong the network lifetime. Due to the resource and energy constraints in WSNs, routing can be considered as a matter of contention in networks. This research proposes a beacon-enabled least-time and energy-efficient routing protocol with single-level data-aggregation using an IEEE 802.15.4. Considering the low complexness and low power consumption it is appropriate for low-rate wireless personal area networks as WSNs. On comparison of the proposed protocol with the popular ad hoc and other WSN routing protocols, the results show that the proposed protocol outperforms the routing protocols in the literature in terms of latency, throughput, and average energy consumption.
Image categorization requires the algorithm to be learned in order to obtain the efficient categorization. The algorithm used for image categorization may misclassify images that are visually similar to the positive ones. Generally, sampling negatives is done at random. In this paper, we have improved Negative Bootstrap in an efficient way to obtain most relevant negatives. To obtain most misclassified visually similar images in a faster way, fast intersection kernel SVM is generalized and used for classification. The accuracy of classified visual concepts is obtained by using the performance metrics. Several different metrics have been used to show the accuracy of relevant negatives. Manual labeling of negatives could be avoided by using the efficient negative bootstrap algorithm.
Modeling visual attention mechanisms has been a very active area of research in past years owing to the challenges it poses. Many models exist, which have been successfully implemented in content based image retrieval systems. Owing to the vast quantities of image data available digitally, services for indexing or retrieving images based on queries have been gaining popularity. In this paper, a novel method is presented for image saliency detection using a more efﬁcient color space model (performance-wise) based on the color distribution of the images instead of the primary visual features. It is done by combining global and local feature extraction into a single method of content detection within an image for purposes of image retrieval, which is proven to be more efﬁcient, as well as taxonomy of various distance metrics used to identify local features. Furthermore, we gauge the performance of these metrics on a 9908 set of test images, based on their precision and recall. The paper has inferred the result by using a set of test images and evaluation methods that can serve to evaluate future metrics.
There is a growing demand for the environmental pollution monitoring and control systems. In the view of ever increasing sources with toxic chemicals, these systems should have the facilities to detect and calibrate the source quickly. Toxic gases are the ones that cause health impact but humans are being exposed to it in various situations. These gases have to be monitored such that increase in normal level of them could be known and proper precaution measures can be undertaken. So, an embedded system is designed using microcontroller with IOT, for the purpose of detecting and monitoring the hazardous gas leakage, which aids in the evasion of endangering of human lives. The hazardous gases can be sensed and displayed each and every second, in proximity with one more sensor for tracking Heart Beats which helps to monitor the condition of the sewer laborers. If both the gases along with pulse detector exceeds the normal level then an alarm is generated immediately and also an alert warning message can be sent to the authorized administrator and as well to the nearest health center to make the sewer laborers feel comfortable with necessary first aid and possibilities with the treatment in case of emergency. Once when the message is received by the health center, they enforce their team with necessary first aid to the current location to save the sewer laborer. Once this system is established for a particular user this will completely become fully automated doesn’t need any other additional people for monitoring and alerting purpose. It has advantage over the manual method in offering quick response time and accurate detection of an emergency.
In applications similar like a social networking services and online games, multiple moving users form a group and wish to be continuously notified with the best meeting point from their locations. We intend a novel monitoring problem, Efficient Notification of Meeting Points (ENMP) for multiple moving users: given a group of moving users U, a set of points of interest (POI) P, ENMP continuously information the optimal meeting point po∈ P to users in U such that their maximum distance toward pois minimized. ENMP is motivated by many applications in social networks, location-based games and massively multi-player on-line games. We propose novel solutions based on safe region technique. Safe regions are a set of geographical regions such that if each user stays inside his/her own, the query outcome will keep on the same, thus avoiding communication between users and the server.
The objective of this research paper is to design a speaker dependent system that determines the gender of the speaker using the pitch of the speaker’s voice. A speaker dependent system is a system which can recognize speech from one particular speaker. The pitch of the speaker’s voice is estimated by applying various pitch estimation techniques, namely FFT, Cepstral Analysis, Autocorrelation and MFCC to correctly determine the gender of a speaker by classifying the pitch of the speaker’s voice based on existing frequency values that were obtained using above techniques. The proposed system can be used in implementations of AI technologies, Internet of Things and various other future
In this modern era of science and technology people depend on technologies than referring to people for any instance. People rely on Smartphone and applications for any gathering of information on any details such as locations, routes, alerts, and so on. But so far end-user needs to install multiple applications for each function such as location, route and alert. Hence the app (aka application) entitled “Route Saver” which is built user-friendly synchronizing all the functions in one application such as location-distant finder, route analyzer, alert generator and contact holder. Each module is developed in a unique way with innovative specialties. First, the query for route request is processed using route APIs to provide all potential navigation paths, which the user can choose based on the priorities on mode of travel. Then, the dynamic mapping of location-based services (e.g., restaurants, tourist attractions) can be used to reduce the manual querying need of the users significantly. Also, the alert module helps to inform the position of the app user to concerned people(s). Furthermore, the user is given the option to check and/or provide review of the points-of-interest requested during search. The experimental evaluation shows that the application achieves high accuracy to pointing out places dynamically with precision
Speech recognition comes under the field of computational linguistics. It includes research and implementation techniques that empower the identification, recognition and translation of speech detected into text by computers. It is used in mobile phones and voice activated systems. Speech recognition is classified as isolated, continuous, dependent and independent. Isolated word recognition has a brief pause between each word spoken, whereas continuous speech recognition does not have any pause. A speaker dependent system only recognizes speech from one particular speaker, whereas a speaker independent system can recognize speech from anyone. The main objective of this paper is to use the technique of speech recognition to detect, translate and identify animal voices. This system consists of two stages training and testing. Training involves teaching the system by building a dictionary, an acoustic model for each word that the system needs to recognize (Offline analysis). Testing stage involves usage of acoustic models to recognize isolated words using a classification algorithm (Online analysis). This system can be used in animal survey processes, voice storage audio book applications to identify different animal voices in the future with more accuracy.
To the date there is a lots of biometric security systems available in the market but has some limitations in it. Most of the security systems are used to distinguish between the people and its persistence. In most of the biometric system user is directly involved such as carrying the related stuff, exposing the physical contact, typing some password, signing etc. Such things can be avoided by using the odour scent as the biometric technique for the security expectation. The objective of this design is to use the odour as the main authentication system tool. This method will show the capability of detecting the human odour and also help to distinguish accordingly, as the scent of a person is unique. Most of the neuroscience has also given the thought of human olfaction and also the sensor systems. As from the survey the odour scent is the combination of the volatile organic component such as the composition of aldehyde, hydrocarbons, ketones etc. Using the mass spectrometry and the electronic nose sensor, the scents are distinguished based on the volatile components and the data are sampled and differentiated on each people in the security system and also it is matched based on the threshold produced by the sensory system. Which give the high profile identification of the potential, user independent security system with biometric scent authentication.
Cloud computing provides a versatile and convenient approach for knowledge sharing, that bring varied edges for each the society and people. however, there exists a natural resistance for users directly source the shared knowledge to the cloud server since the info} usually contain valuable information. Thus, it’s necessary to put cryptographically increased access management on the shared knowledge. Identity-based cryptography may be a promising cryptographical primitive to make a sensible knowledge sharing system. However, access management isn’t static. That is, once some user’s authorization is expired, there ought to be a mechanism that may take away him/her from the system. Consequently, the revoked user cannot access each the antecedently and sub- quietly shared knowledge. to the current finish, we tend to propose a notion referred to as revocable-storage identity-based cryptography (RS-IBE), which might offer the forward/backward security of cipher text by introducing the functionalities of user revocation and cipher text update at the same time. Moreover, we tend to gift a concrete construction of RS-IBE and prove its security within the outlined security model. The performance comparisons indicate that the projected RS-IBE theme has blessings in terms of practicality and potency, and so is possible for a sensible and efficient data-sharing system. Finally, we offer implementation results of the projected theme to demonstrate its utility.
Streaming Media is a multimedia that is presented to an end user which is constantly received by while being delivered by a provider. Amazon Web Service (AWS) is a collection of remote computing services (also called web services) that together make up a Cloud computing platform, offered over the Internet by Amazon.com. The most central and well-known of these services are Amazon EC2 and Amazon S3. The service is much faster, scalable and cost effective than building a physical server farm. In the existing system, the media streaming is done in computers and it is not in use for common people. Therefore this system is proposed, to take media streaming to every user who uses smartphones.
Password authentication, often used for providing secured service, tend to face problems such as entering the incorrect password while logging in or while encountering an unauthorized access. The proposed system allows the user to choose a meaningful, sensible password which is easy to remember than the regular pattern of alphanumeric characters. It can be implemented on a range of mobile applications and devices, enriching the user’s convenience since security is an important factor to be considered in today’s world. To avoid the attackers from observing the password when the user is inputting, the system implements a technique termed Pass Matrix wherein the rows and columns filled with data. The system gives no clue for attackers even after the camera-based attacks. Experimental results are proved to show no sign of attacks, which portrays its efficiency. The system also provides features to access the user’s account if he/she forgets the password. So, it can be concluded that the proposed system provides better resistance to shoulder surfing attacks thereby maintaining usability.
Data mining is the extraction of present information from high volume of data sets, it’s a modern technology. The main intention of the mining is to extract the information from a large no of data set and convert it into a reasonable structure for further use. The social media websites like Facebook, twitter, instagram enclosed the billions of unrefined raw data. The various techniques in data mining process after analyzing the raw data, new information can be obtained. Since this data is active and unstructured, conventional data mining techniques may not be suitable. This survey paper mainly focuses on various data mining techniques used and challenges that arise while using it. The survey of various work done in the field of social network analysis mainly focuses on future trends in research.
Several military operations require enlarged protection of confidential data including access control methods that are enforced crypto-graphically. In many cases, it is desirable to provide differentiated access services such that data access strategies are defined over user attributes or roles, which are managed by the key authorities. Mobile nodes in military environments such as battle fields may have intermittent network connectivity and frequent partitions. Disruption-tolerant network provides efficient way for soldiers to communicate using wireless devices and also gives access to the confidential information or commands. In this scenario, the most challenging issues are enforcement of authorization policies and policy updates for secure data retrieval. So we are using Cipher textpolicy attribute-based encryption to solve access control issues.However, the problem of applying CP-ABE in fragmented DTN introduces several security and privacy challenges with various fields such as attribute revocation, key escrow, and categorizing of attributes issued from different authorities. We demonstrate how to apply the proposed workings to securely and smoothly manage the confidential data distributed in the disruption-tolerant military network.
The generation of information is growing at a surprising pace. The emotional ascent of unstructured information like photographs, recordings and online networking has introduced another type of non-social databases and which are named as “Big Data”. In 2012, the measure of data put away overall surpassed 2.8 Zetabytes. By 2020, the aggregate sum of information put away is required to be 50 times bigger than today. Big Data must be prepared and analysed to deliver potential ideas and extreme information must be comprehended from this sea of information. A famous system Hadoop is utilized as of now to process such huge information. Here we execute LIBRA with various approaches that altogether lessen the information skew-(a typical issue in mapreduce) by element part methodology without pre-processing the whole data. To give question preparing, another algorithm Block-Chain is introduced.
Digitized India is used to connect rural areas with high speed Internet. As a result, it is used to reduce crime, manual power, documentation and also increases the job opportunities. Nowadays people are facing many problems when they forget to carry the driving license and also to reduce the corruption, the proposed system combines the driving license with Aadhar card. The details of driving license and Aadhar card data can be combined using the MapReduce Counters. It automatically aggregated over Map and Reduce phases. It is used to create a tool that manages the handling of license using unique identification associated with each individual. It helps the user to travel various places without having the license. So the proposed system will make the digitization of data on a large scale for easy and quick access throughout the India. Sqoop is a tool intended to exchange information amongst Hadoop and social databases. Sqoop utilizes MapReduce to import and export the information, which gives parallel operation and in addition adaptation to noncritical failure. As the result of parallel operations time utilization for transferring the data get decreased radically.
Nowadays, Internet of things plays a vital role in all engineering fields and it is a chain of physical devices consolidated with electronic components, software, sensors, actuators and structural connectivity which empowered to the objects to relate and switch the data. The intention is to give security to image transferred through the internet to other devices connected in the common network and it is provided by steganography and additional authentication is done using biometric iris recognition. Data is sent to web server which act as the front end. A device which is also in the network, receives the image which is obscured by steganography and decrypt them to obtain data. The server side programming includes capturing an image by the raspberry pi camera.LSB image steganography is acted on the picture and passed to the server through a webpage. The webpage created is configured to rule the GPIO pins remotely. In the client side, the image is obtained and iris recognition is done. If authenticated then access is given through the webpage and the indication system is used to convey for the user.
Micro strip patch antennas are widely used in wireless applications in recent years. The C-band frequencies of 5.4 GHz band [5.15 to 5.35 GHz, 5.47 to 5.725 GHz, or 5.725 to 5.875 GHz, depending on the region of the world] are used for IEEE 802.11a Wi-Fi and cordless telephone applications, leading to occasional interference with some weather radars that are also allocated to the C-band. The proposed slotted back to back E-shaped antenna designed for 29.4*29.4mm operates at a frequency of 5.4GHZ for C band application such as Wi-Fi. The substrate material of the antenna is Flame Retardant (FR-4), dielectric constant 4.4 and thickness 1.6mm. The basic theory and design are analyzed, and simulated using Advanced Design System Software ADS. The main objective of the work is to improve gain, return loss and radiation.
Tremendous growth of multimedia technologies mandates the need for high quality images. Thus fast and efficient noise removal technique is the need of the hour. Nonlinear filters have shown their supremacy in removing the outliers from a signal affected by non-Gaussian noise, such as clicks, scratches, salt-and pepper impulses etc., Median filter is the most sought after non linear filter known for its excellent noise reduction capability. A modified selective one dimensional median filter design is proposed in this work which is aimed at reducing the power consumption. Proposed design is a word-level filter; the samples are stored in descending order in the window of size N. When a sample enters the window, the oldest sample is removed, and the new sample is inserted in an appropriate position to preserve the sorting of samples. The throughput of the design is increased by performing the deletion and insertion of samples in the same, so that the median output is generated at each cycle. The simulation results has shown reduction in power and delay thereby improving the throughput.
Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. However, these techniques are severely hampered by motion artifacts and are limited to heart rate detection. To address these shortcomings we present a new ECG wearable that is similar to the clinical approach for heart monitoring. Our device weightless and is ultra low power, extending the battery lifetime to over a month to make the device more appropriate for in-home health care applications. The device uses two electrodes activated by the user to measure the voltage across the wrists. The electrodes are made from a flexible ink and can be painted on to the device casing, making it adaptable for different shapes and users. Also show the result of heart rate of beats per minute (bpm) based on the R-R interval (peaks) calculation. That means whether the heart function is normal or abnormal (Tachycardia, Bradycardia).
Internet of things (IoT) has become a major technology in this modern life. Real time system is used for constant monitoring and effectively secure. Accidents often occur frequently nowadays and the fatality rate has been drastically increased about 4.6% on the last year. Half of the people killed in these accidents are youngsters of teenage and middle aged. In India road accidents has become common and the reasons are due to poor driving and badly maintained roads and vehicles. This system provides vehicle control and navigation for the user. In this paper, we present an IoT enabled system to avoid the vehicle accident and theft. Using IoT in designing some special services can make a lifesaver system. In this paper, we have presented an IoT enabled approach that can provide emergency communication and location tracking services in a remote car that meets an unfortunate accident or any other emergency situation. Immediately after an accident or an emergency, the system either starts automatically or may be triggered manually. Depending upon type of emergency it initiates communication and shares critical information. Provision of interactive real-time multimedia communication, real-time location tracking etc. have also been integrated to the proposed system to monitor the exact condition in real-time basis. The system prototype has been designed with Raspberry Pi 3 Model B. emergency situation. Immediately after an accident or an emergency, the system either starts automatically or may be triggered manually. Depending upon type of emergency it initiates communication and shares critical information. Provision of interactive real-time multimedia communication, real-time location tracking etc. have also been integrated to the proposed system to monitor the exact condition in real-time basis. The system prototype has been designed with Raspberry Pi 3 Model B.
This paper discusses the concept of a smart wearable device for little children. The major advantage of this wearable over other wearable is that it can be used in any mobile phone and doesn’t necessarily require an expensive smart phone and not a very tech savvy individual to operate. The purpose of this device is to help parents locate their children with ease. At the moment there are many safety wearable devices in the market which helps to track the daily activity of children and also help find the child using Wi-Fi and Bluetooth services present on the device. But Wi-Fi and Bluetooth appear to be an unreliable medium of communication between the parent and child. Therefore, the focus of this paper is to have an SMS text enabled communication medium between the child’s wearable and the parent as the environment for GSM mobile communication is almost present everywhere. The parent can send a text with specific keywords such as “LOCATION” “TEMPERATURE” “UV” “LIGHT” “BUZZ”, etc., the wearable device will reply back with a text containing the real time accurate location of the child which upon tapping will provide directions to the child’s location on google maps app and will also provide the surrounding temperature, UV radiation index so that the parents can keep track if the temperature or UV radiation is not suitable for the child. The secondary measure implemented was using a bright Light and distress alarm buzzer present on the wearable device which when activated by the parents via SMS text should display the light signal brightly and sound an alarm which a bystander can easily spot as a sign of distress. Another feature added to the device is HEART BEAT SENSOR which will monitor the child’s heart beat and sends an intimation message to the parents once its removed from the child. Hence this paper aims at providing parents with a sense of security for their child in today’s time.
Composite of data from multiple sensor nodes is usually done by simple methods such as averaging or, more sophisticated, iterative filtering methods. However, such aggregation methods are highly vulnerable to malicious attacks where the attacker has knowledge of all sensed values and has ability to alter some of the readings. In this work, we develop and evaluate algorithms that eliminate or minimize the influence of altered readings. The basic idea is to consider altered data as outliers and find algorithms that effectively identify altered data as outliers and remove them. Once the outliers have been removed, use some standard technique to estimate a true value. Thus, the proposed composite data algorithm operates in two phases: removal of outliers and computation of an estimated true value from the remaining sensor data. Extensive evaluation of the proposed algorithms shows that they significantly outperform all existing methods.
A single band E-Shaped Patch antenna with Defective Ground Structures (DGS) was proposed. The overall dimension of the antenna is (32*31.5*1.64) mm. This antenna produces bandwidth ranges from (2.3 to 2.5) GHz, which supports ISM band application. This provides reflection coefficient about -32dB respectively. This antenna is designed using FR4 substrate with dielectric constant 4.4. The various parameters like Reflection coefficient, VSWR, Directivity, radiation pattern. The antenna is simulated using EM simulator)
In this Paper, aim is to achieve a narrow bandwidth filter. For that coupled line filter is good choice. Coupled-line filter is designed on microstrip for its compactness. Microstrip dimension are calculated using synthesis technique formula. A Coupled-Line Microstrip Filter is designed for centre frequency 2.4GHz and it is made up of FR-4 material having permittivity Єr=4.4. Coupled line filter demonstrate the fourth order of the Chebyshev elements and its response corresponds to bandpass filter. The geometry is analysed by using Computer Stimulation Techniques (CST) software.
Rectangular Micro strip patch antenna with Defective Ground Structures (DGS) is proposed in this paper. The overall dimension of the antenna is (130*130*1.64) mm. The antenna produces resonance at 2.48 GHz, 4.01 GHz and 4.64 GHz which supports WLAN applications. The proposed antenna gives the reflection coefficient of -16.8dB, -36.94dB and -27.73dB respectively in simulation. The directivity values in simulation are 7.7dBi, 3.8dBi and 6.3dBi respectively. The antenna is designed using FR4 substrate with a dielectric constant value of 4.4. By using DGS, bandwidth is enhanced. The various parameters like reflection coefficient, directivity, bandwidth, radiation pattern are simulated using EM simulator.
Wideband, planar antenna of I shaped with outer slit for ISM application In our work, we presented a concept of designing antenna for 2.4GHZ. The special shaped patch antenna is used to attain ISM bands. It is an I shaped antenna, along with a tilted and inverted two u shaped antenna patched over it. One thick inverted U shaped antenna, tilted with 450 and another is of thin inverted u shaped antenna that tilted 900 in accordance with a previous tilted patch, that is about 450 to I shaped antenna but on opposite side of thick patch. It is connected to thick U shaped patch not with an I shaped patch. All rotation and tilting are done in horizontal axis. A 6*6 square metallic patch antenna was designed in back for simple frequency selecting purpose.
A frequency-reconﬁgurable antenna designed using metasurface (MS) to operate at around 5 GHz is studied and proposed. The frequency-reconﬁgurable metasurfaced (FRMS) antenna is composed of a simple circular patch antenna and a circular MS with the same diameter of 40 mm and implemented using planar technology. The MS is placed directly atop the patch antenna, making the FRMS antenna very compact and low proﬁle with a thickness of only 3.048 mm. The MS consists of rectangular-loop unit cells placed periodically in the vertical and horizontal directions. Simulation results show that the operating frequency of the antenna can be tuned by physically rotating the MS around the center with respect to the patch antenna. The MS placed atop the patch antenna behaves like a dielectric substrate and rotating the MS changes the equivalent relative permittivity of the substrate and hence the operating frequency of the FRMS antenna. Measured results show that the antenna has a tuning range from 4.76 to 5.51 GHz, a fractional tuning range of 14.6%, radiation efﬁciency and a realized peak gain of more than 80% and 5 dBi, respectively, across the tuning range.
The main aim of the proposed project is to dampen water efficiently in a cognitive approach for the agriculture land using IoT and also measures the Irrigation Efficiency (IE). The water needed for the crops should be properly irrigated for enriching the irrigation efficiency of the field. Using soil moisture sensor and water level indicator in which a threshold value is thrown into and the irrigation area is monitored continuously. The conductivity of the top soil increases as the volumetric wet substance increases. The water level indicator is maintained above the threshold value and it is is indicated when it is below the sensored value. The sensored information should be given as an analog key in of the Node mcu Arduino board. The sensor records values are between 0 (perfectly dry) and 900 (100% saturated) which is displayed in the sequential display unit of the workstation in which it is connected. Thus the real instant data of the water substance of the soil is taken as the input and the motor is made to function based on the throw values between 0 and 900. This device collects data continuously for an extended period of time and functioned as an alert device when soil moisture dropped below the specified value. The complete system is controlled and monitored through internet. The board has the capacity to transmit data using both the SPI and I2C protocols. Also the irrigation efficiency of the system is determined at the particular period of time that takes into account the micro-efficiencies of the irrigation water used. About 80% of the water is saved using this smart advanced irrigation system.)