Connectivity Lezyne’s Mega XL GPS cycle computer comes with advanced connectivity options with the device automatically syncing to your smartphone via Bluetooth Smart. This connectivity allows you to receive texts, emails, and phone call alerts right to your cycling computer’s display. You can easily download all your ride files via the plug-and-play flash drive technology and upload directly to GPS Root website for ride analysis. The Mega XL will also auto-sync to Strava, TrainingPeaks, and Today’s Plan plus using Bluetooth Smart or ANT+ you can connect additional sensors and kit. GPS Using the ultimate in GPS and Glonass technology you’ll receive the very best in navigation and advanced tracking systems. The screen comes with preloaded maps and offers customisable route building allowing you to adventure further afield without getting lost. A built-in barometer and accelerometer also provides key tracking and weather alerts. Display The super large 2.7 inch display comes with 240 x 400 high-resolution and provides a 50-percent larger display than previous models such as the Super GPS. The display can also be completely turned and offers you either vertical or horizontal viewing modes. You can completely customise what data appears on the display and the computer comes with a back light and full colour display. Loaded The Mega XL GPS – Loaded Bundle comes with all the sensors and fittings you need for the fullest and most immersive cutting-edge cycling experience. The kit includes: Mega XL GPS computer Heart Rate Flow Sensor Speed/Cadence Flow Sensor Direct X-Lock Mounting System Micro USB charging cable
Context Aware Reminder System ab 49.9 € als Taschenbuch: Activity Recognition Using Smartphone Accelerometer and Gyroscope Sensors Supporting Context-Based Reminder Systems. Aus dem Bereich: Bücher, English, International, Gebundene Ausgaben,
The surge for silicon accelerometers with low form factor-g and low noise-power-voltage interfacing readout systems are of paramount interest for the next generation's light-weight, low-cost Inertial Measurement Units (IMU's) and microgravity measurement systems, opening the scope for a wide range of low-power applications in VLSI-MEMS technology. This key-informative book gives a head start for reader to participate in emerging fields of application. It deals with the designing, modelling, simulating & analyzing the low power- low noise - high performance generic interfacing system that utilizes switched capacitive technique to read out electro-mechanical accelerometer values within the range of ±2g. The mixed-signal topology is developed to be highly programmable using MATLAB/SIMULINK environment to analyze the noise contributors and system-level circuit non-idealities to make the model a reliable tool in identifying the performance limits of the mixed-signal embedded high speed circuitry to ensure power & noise reduction. This book is for all enthusiastic readers & innovators guiding them to build more realistic & reliable systems for VLSI World.
Strong dependence of surface plasmon resonance (SPR) on coupling parameters offers new varieties of sensing mechanisms in nano and micro-scale engineering fields. In this study, design, fabrication and characterization of MEMS displacement sensors that utilize angular dependence of grating coupled SPR condition are explored. Several surface plasmon polariton (SPP) excitation mechanisms are reported in the academic literature. One of them which is quite adaptable to microelectromechanical systems is grating coupling scheme. In this scheme, thin metallized grating structures are particularly designed depending on the desired wavelength and the angle of incidence of the SPP excitation light. Various lithographic techniques (nanoimprint, electron beam and optical lithography) are used to nanofabricate those certainly defined gratings. MEMS displacement sensor designs relying on the principle of angular displacement detection scheme are developed. In addition, a MEMS accelerometer design with plasmonic readout with nano-G noise floor is presented. Novel arrayed sensors combining the sensitivities of plasmon resonance and micromembrane type sensors may provide unprecedented performance.
Context: Sensor base data is being used for many purposes in designing various memory aid systems for cognitive impaired people. Different memory aids or reminder systems are based on various technologies such as NFC, accelerometer, GPS and gyroscope. Smart phones are equipped with such sensors and can be used for assistance of persons. In this study we use smart phone sensors in order to design a context aware reminder system to assist cognitive impaired people.
Human machine interface with dedicated software using sensors for energy harvesting. Nowadays Human-machine interfacing (HMI) motivated many studies to develop systems and devices that were able to transfer analog commands from the user's body to machines through movements. Natural evolution provided human beings with one of the most efficient mechanical interfaces with the outer environment through hands. People use their hands to interact with tools and other people every day. People in nowadays use finger movement in hand to generate energy. In this model to harvest the energy through finger movements with the support of microcontroller, piezoelectric sensor, 3-axis accelerometer.
Voice recognizing wheelchair is an automatic wheelchair for physically disabled people, which consist of dependent user voice recognition system, ultrasonic and infra-red sensor systems. In this way we have obtained a automatic wheelchair which can be driven using voice commands and with the possibility of avoiding obstacles by using infra red sensors and down stairs or hole detection by using ultrasonic sensors. The wheelchair has also been developed to work on movement of accelerometer which will help for the person whose limbs are not working.
With the advent of miniaturized sensing technology, which can be body worn, it is now possible to collect and store data on different aspects of human activities under the conditions of free living. This technology has the potential to be used in automated activity profiling systems which produce a continuous record of bodily activity patterns over extended periods of time. Such activity profiling systems are dependent on recognition algorithms which can effectively interpret body worn sensor data and identify different activities. The automated recognition of bodily activities (stationary, walking, running, jogging) using body worn accelerometer data is a challenging area of work. In this book existing activity recognition system were discussed. In Existing activity recognition systems suffer from several obvious practical limitations such as the location and nature of sensors that people will tolerate. Other issues include ease of use, discretion, cost, and the ability to perform daily activities unimpeded. The results are getting from the Accelerometers with different subjects are collected through pc and can be analysed by Matlab software by activity variance and DT algorithm.