This chapter introduces the background of the project. The selected project is named as Hand Sign Language Translator using Motion Sensor. Basically, in this part, the concept of the projects as well as the objectives need to be achieved be discussed and stated clearly. Besides, limitations and constraints were also imposed on the project in order to manage the scope of project. Last but not least, the purposes of having this project and the impacts the project can bring to the society upon implantation will also be discussed thoroughly.
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The main conclusion of this paper is that motion sensing technologies have been developed rapidly over the past years and many game titles are available, which seem to be exploited for educational purposes. One can find quite an amount of ideas and teaching material, although not always tested within the context of carefully designed research approaches. Nevertheless, the main characteristic of the digital age in which we live is that people create and share knowledge, information and ideas. Thus, many internet based communities are available, especially for educators willing to try innovative approaches. The innovative technologies have the potential to enhance the students’ interest for knowledge and enlarge the educational motives. Since the young learners are considered as digital natives nowadays, it is crucial to capture their interest with technologically innovative ideas. As far as the latter is concerned, the motion sensing technology usage in education could transform a student to a young programmer who thinks, designs, evaluates, reflects and adjusts solutions. Moreover, motion sensor could enhance young students’ motor skills and introduce new ways of problem solving skills development. It is obvious that the corresponding research has still a long way to go.
A blurred image can be recognized as a convolution function of a sharp image and a blur kernel or PSF. So in order to recover the sharp image it is needed to know the PSF function which causes the motion blur. The unknown blur kernel estimation is called as the Blind deconvolution. Most of the deblurring techniques make use of these concepts. Few methods such as, Winner Deblur and Luci-Rechard uses sensors to calculate the PSF. In this paper some reading of inertial motion sensor is considered with the value of LEN and Theta to calculate the PSF. At the same time motion blurred images dataset is considered for applying the Blind De-convolution, Winner for the results to calculate best suitable parameters of good quality image output.
The user’s hand actions are first captured by the leap motion sensor. The biometric data derived from derived from the user’s hand. The data pre-processing occurs wherein by storing the starting position and the offsetting the signature position by the starting position .Data analysis occurs with the help of the DTW (Dynamic time warping algorithm). The initial user template is generated for further authentication purposes.
Abstract: Internet of things (IoT) has become common, each and every thing applies Internet, and everyone is familiar with internet and mobile phones. This paper is all about implementation of a smart classroom. A smart classroom is one which has Automatic Attendance, Safety, Security, Surveillance and teaching methods, also Energy i.e., Power management. The system uses up an efficient setup which has a Raspberry pi (Instructor/Commander) for the system and sensors like Fire Sensor, Face Detector, LDR, Motion Sensor, Finger-Print Sensor are being utilized. The system becomes smart since it is automatic, uses IoT and easy to access by a common man. The system is capable of monitoring and taking attendance, Security alert, Fire alarm and rescue.
The further experiments are to be made to improve the speed of transmission and the distance over which it is transmitted. Increasing the speed of transmission, the seamless video can be observed at the receiver end. In addition, the PIR motion sensor can be included to reduce the overall power consumed by the system. Further improvements can be done to increase the resolution of the video.
In order to deploy a motion sensor, there are many ways. They are Consider a scenario, i n a store where a light beam crossing the room near the door, and a photo sensor that resides on the next side of the room. Whenever a customer crosses the beam, the in-built photo sensor captures the amount of change of light and starts ringing the bell. Most of the grocery stores have door openers that operate automatically and use a very simple form of radar in order to detect the movements near the door. There is a box above the door which sends a burst of microwave radio energy and waits till the reflected energy to bounces back.
Smart Home, meaning a house that comes with automation, is an intelligent house or IT house. Intelligent residential services consist in providing support to ensure automated and efficient use of various facilities in an intelligent house. For example, Hunhammar  suggests that an intelligent house should include control and management services such as energy saving, safety management, emergency management, crime prevention, and fire protection. Intelligent service consists in providing a residential service that uses IT with such features as situation recognition, real time, personalized, and sensing to sensitively recognize situations arising in every corner of a house and thereby promptly respond through analysis and prediction. With the development of IT, research is actively carried out on ‘Internet of Things (IoT)’ that can share information through wireless networking not only in various home electronics and electronic devices but also in various areas such as healthcare, remote meter reading, smart home, and smart car. IoT refers to intelligent technology and network service that provides mutual communication that deals with information between human and object, object and object . IoT is helpful in more accurately and promptly figuring out a situation. For example, it makes it possible to improve the accuracy of decision-making through communication between CCTV and motion sensor, motion sensor and floor pressure sensor. One advantage of smart technology lies in saving much manpower involved in caring for elderly people by reducing their dependence on other people. To reduce dependence of elderly people, it is indispensable to provide appropriate services for them. So far, vitalization of smart home has been unsatisfactory, because it hasn’t been able to provide appropriate services that consider its users. In this light, as regards provision of appropriate residential services, observation of elderly people’s behaviors makes an effective method. Lee  suggested that we should fuse together in various ways inferential methods that are based on resident behaviors and services in order to predict and respond to complex human behaviors. In “Smart Homes for Patient at the End of Life, Demiris  presented types of monitoring such as functional monitoring, safety monitoring, physiological monitoring, and security monitoring. A description of monitoring should be helpful in conducting a systematic research. Specifics of monitoring are as seen in Table II. Types of monitoring may be explained as follows.
The computer vision-based method is one of the several kinds of fall detection techniques being developed or applied in our life. A visual-based fall detection method could be enhanced through the external supports such as motion sensors, and to raise robust performance in a fall detection and to operate for the validation and correlation of the two subsystems, a data fusion algorithm technique can be used. These visual-based methods work eﬀectively in an indoor environment, but yet still becomes hard to realize in the outdoor environment as the deployment of cameras is always limited .
The three commonly used terms are absolute humidity, dew point, and relative humidity (RH). It is based on an interdigitated or bifilar winding. After deposition of a hydroscopic polymer coating, their resistance changes inversely with humidity. The impedance change is typically an inverse exponential relationship to humidity. Resistive humidity sensors usually consist of noble metal electrodes either deposited on a substrate by photo resist techniques or wire-wound electrodes on a plastic or glass cylinder. The substrate is coated with a salt or conductive polymer. When it is dissolved or suspended in a liquid binder it functions as a vehicle to evenly coat the sensor. Alternatively, the substrate may be treated with activating chemicals such as acid. The sensor absorbs the water vapour and ionic functional groups are dissociated, resulting in an increase in electrical conductivity. The response time for most resistive sensors ranges from 10 to 30 s for a 63% step change. The impedance range of typical resistive elements varies from 1 k to 100 M .
As previously mentioned, the wavelet transform can be used for slamming analysis in two ways, either as an identifier of slamming occurrence through the detection of a slamming signature, or for the identification of modal parameters during certain time intervals. Achieving both goals in one analysis is impossible and it is much better to perform the analysis twice, firstly with a high time resolution mother wavelet and secondly with a high frequency resolution mother wavelet. Although the available time series has 100 % time resolution, slamming detection is extremely difficult, especially for small slams and for those slams where the initial impact is hidden in the whipping response of a previous slam. The centre bow vertical acceleration record is the most suitable for slamming occurrence detection as this sensor, dominantly, precedes all other sensors in the time response to slamming, while the strain gauges are the best sensors to identify the normal modes. To show the validity of this procedure, samples of vertical bow acceleration record and four strain gauges (the three keel gauges and the vertical steel post gauge) between the time instants 958 and 968 s are studied. The record shows two consecutive slamming events, Figure 2.25 (a). None of the time series display clear slamming behaviour of initial impact
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Therefore, in this paper, we designed a system to prevent dementia by applying ICT technology. For this purpose, we applied dragon flight game using motion recognition to prevent dementia. Game training using ICT technology has been found to improve the cognitive control ability of the elderly. In other words, playing games steadily for about one hour a day can improve the aging of the cognitive function. In this paper, we apply a method that induces interest by using drones rather than simple digital games. As a result, it is a method of generating a drone control signal based on motion data of the elderly. Also, it is a method to control the drone by connecting with Ground Control Station (GCS) with the generated signal. When the elderly wears the motion recognition sensor and proceeds with the motion, the corresponding motion data is measured. The motion data is converted into data usable in the drone. Then, the conversion data is transmitted to control the drone. By applying these methods, it is possible to prevent dementia by controlling the drones by motion. Figure 1 shows a general outline of the dementia prevention system of the elderly applying the dragon flight control method through motion recognition.
The sine waves at 46 MHz and 2 MHz were adopted and input to the mixer which then output the compositional signal. There are two major peaks at 44 and 48 MHz, two secondary peaks at 40 and 52 MHz, and a minor peak at 2 MHz in the frequency-domain of the output signal from the mixer. The emitted electromagnetic waves from the antenna sensor were collected at the receiver coil and then transmitted to the oscilloscope for subsequent FFT transformation. As the receiver coil possesses good filtering performance, the peak at 2 MHz is depressed and there are eight obvious peaks at 40 MHz, 42 MHz, 44 MHz, 46 MHz, 48 MHz, 50 MHz, 52 MHz and 54 MHz in the frequency domain, as shown in Figure 10. The antenna sensor was bent at angels of 0°, 20°, 40°, 60° and 80°. The first eight higher peaks were acquired for establishing the characteristic matrix of the antenna sensor , as shown in Figure 11. Five test angles (0°, 20°, 40°, 60°, 80°) were set on the antenna sensor and the identified results are shown in Figure 12. The angle at the calculated minimum distance is identified as the bent angle of the antenna sensor. It is found that this method can be used to precisely identify the bent angle of the finger posture.
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A systematic review and meta-analysis of studies com- paring lumbo-pelvic kinematics in people with and with- out back pain demonstrated significant limitations in the included studies, specifically a lack of detail or standardization between studies on the criteria used to define participants as those with LBP or without LBP . Furthermore, the reliability of the most common means of measuring lumbar sagittal motion (plurimeter V double inclinometer, the carpenter double inclinom- eter and the computerized single sensor inclinometer) was found to be greatly varied, falling below clinically desirable levels with errors primarily attributed to the examiner . Using 3D lab-based motion analysis,
Sign language being the only communication means for deaf-dumb community hampers their interaction with the normal people who lack the knowledge of sign language. This paper has the potential of minimizing this communication barrier by working as an automated translator and converting sign language directly into vocal and textual format for the understanding of normal people using various MEMS sensor, PIC microcontroller. The input data glove detects the hand gesture done by the deaf-dumb person wearing it and provides the analog input to the microcontroller for further interpretation according to the database and the final output is observed on the LCD display and the speaker. Thus, hand gesture can be automatically converted with the help of this system into understandable form for the normal person.
The proposed prototype system is implemented and tested for the desired functionalities. Fig. 8 shows the test bed. The green and red LEDs are employed to indicate the temperature above optimal level and the alarm respectively. The function of mechanical switch is done manually through a connecting wire. The system made 5 calls to a pre-specified cell phone number in 5 test runs which yields a hundred percent success rate. The whole test procedure is done in a laboratory having the mentioned criteria for optimal performance. Based on several experiments conducted under various conditions, it is verified that this system can resolve the presence of any warm body within the coverage area and execute subsequent actions. In order for a PIR sensor to work well most of the time, it is designed with certain limitations. A PIR sensor cannot detect a stationary or very slowly moving body. If the sensor was set to the required sensitivity, it would be activated by the cooling of a nearby wall in the evening, or by very small animals. Similarly, if someone walks straight towards a PIR sensor, it will not detect them until they are very close by. PIR sensors are temperature sensitive - they work optimally at ambient air temperatures of around 15-20 degree Celsius. If the temperature is over 30 degree Celsius, the field of view narrows and the sensor will be less sensitive. Alternatively, if the temperature is below 15 degree Celsius, the field of view widens and smaller or more distant objects will activate the sensor. On cold nights, the difference in temperature between a person, e.g. normal body temperature is 37°C and the outside air temperature is relatively large, giving an apparent increase in performance of the sensor. On hot nights, this difference in temperature is relatively small and a decrease in performance of the sensor can be expected . Moreover, the PIR sensors are sensitive to exposure to direct sunlight and direct wind from heaters and air conditioners. Precaution is required if there are pets in the house. PIR's are sensitive enough to detect dogs and cats. There are special lens available or a tape can be put on lower part of the existing lens, so as to avoid detection close to the ground. At the same time, it should be kept in mind that the intruder can also crawl and avoid detection. So placement and subsequent testing of PIR sensor modules' is a must to avoid false alarms. These factors need to be kept in mind to ensure the proper operation of this system.
In the present scenario, monitoring those resources and our own belongings by ourselves is of prime concern. The system here aims in implementing an online facility for monitoring our home and the equipment status at any instant of demand. Here, an online monitoring system is developed that enables such a monitoring activity. Here online monitoring and automation is facilitated for light detection, water level detection and unauthorized motion detection. The system implemented here uses the latest embedded processor of Intel namely Intel Galileo. The system serves more advantageous when we are apart from our home for a short period like for one week so. In such periods, it seems to be difficult for employing a person for monitoring the home. While considering the application for other periods this seems to be helpful in monitoring home and thereby avoiding the unwanted wastage of resources like water and electricity.
Micromechanical sensors represent a new branch of chemical sensing that utilizes a microfabricated spring (cantilever), as originally applied in atomic force micro- scopes (AFMs), for the recognition of interfacial mass- and charge-transfer processes with very high sensitivity. A detec- tion system based on cantilever micromechanical behaviour already exists and is identical to that employed in AFMs (Jalili and Laxminarayana, 2004). This system has allowed the detection of analytes in concentrations down to the pico- molar and sub-picomolar levels to become feasible in a va- riety of processes, including deposition/dissolution, adsorp- tion/desorption (Ji et al., 2001), solution pH changes and surface-confined charge-transfer reactions (Tabard-Cossa et al., 2005). For detection, both bending- and frequency- readout micro-lever sensors can be employed (Battiston et al., 2001). Further development will be focused on attempts to construct cantilever arrays (Lang et al., 2005) modified by various receptors to increase the selectivity of the sensor re- sponse (Grogan et al., 2002) and to gain the ability to perform multicomponent analysis in a single step. The major advan- tages of microcantilever array sensors are their micrometre- scale size, high sensitivity and short response time (Berger et al., 1997).
Outside of the entertainment space there have been several papers examining the prospect of more detailed motion and position tracking of an individual through the use of worn IMU sensors. Previously, body motion tracking has been pri- marily accomplished through optical means due to its high level of precision. This has been further bolstered by the de- velopment of Microsoft's Kinect system. Though the Kinect lacks the precision of advanced multi-camera systems, it al- lows for easy motion tracking at a more economical cost. The- se optical systems have major limitations though, as they re- quire constant line of sight of the subject and self-occlusion can be problematic. Camera-based systems also suffer when there are poor lighting conditions, require the user to stay within a very stringent operational area and typically are opti- mized for indoor use only.
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The completed working model of our project is as shown in the above figure 4.2 1. The working model of this project is at first the Wi-Fi should be connected and when an employee or manager enrols him/her fingerprint in the fingerprint module door will be open and they have the access to enter the office and the notification will be sent through the mail to the manger as this employee is present. As soon as they entered inside the office, motion is detected by the motion detector and all the lights and fan will be ON state as the presence of the person. If security fingerprint detected all the lights and fan will be OFF shows that the office is closed. Inside the office LDR and MQ2 Gas sensor detected buzzer will be ON and notification will be sent to the security people and mail will be sent to the manager. We can also control the lights and fan through Blynk android application.