Abstract:
A computing platform for intelligent development, deployment and management of vehicle telemetry applications is disclosed herein. Further, the present disclosure provides a method and system that enables provision of Intelligent Transportation Service on the Cloud-based Platform that facilitates creation and deployment of vehicle telemetry applications configured for enabling traffic measurements, traffic shaping, vehicle surveillance and other vehicle related services.
Abstract:
Tracking motion using inertial sensors embedded in commercial grade wearables like smartwatches has proved to be a challenging task, especially if real-time tracking is a requirement. Present disclosure provides system and method wherein data from sensors are obtained and scaled. Further, Euler Rodrigues Matrix (ERM) is generated based delta value obtained using sensor data. The scaled sensor data and ERM are used for generating feature vectors. Windowing technique is applied for subsets of feature vectors to obtain label for each window and machine learning model is trained with the label and window. Further, during real-time, sensor data is obtained, and steps of ERM, feature vectors generation, and application of windowing technique are repeated, and coordinates are estimated for each window in real-time based on which trajectories are tracked in real-time for each window.
Abstract:
Any sensing system is faced with triangle of dilemma between accuracy, latency and energy. High energy and high latency sensing systems are often very accurate but less useful. Embodiments herein provide a method and system for edge based sensor controlling in the IoT network for event monitoring. The system disclosed herein applies a hierarchical sensor selection process and adaptively chooses sensors among multiple sensors deployed in the IoT network. Further, on-the-fly changes operation modes of the sensors to automatically produce the best possible inference from the selected sensor data, in time, power and latency at the edge. Further, sensors of the system include a waveform and diversity control mechanism that enables controlling of an excitation signal of the sensor.
Abstract:
The present disclosure provides wearable apparatus and method for calculating drift-free plantar pressure parameters for gait monitoring of an individual. Most conventional techniques use different kind of sensors placed in in-sole based wearable apparatus but are costly and not effective in calculating accurate plantar pressure parameters. The disclosed wearable apparatus uses off-the shelf piezoelectric sensors that are widely available in market with less cost. The drift-free plantar pressure parameters are calculated using drift-free static pressure data obtained by numerically integrating acquired dynamic sensor data from the piezoelectric sensors, using a LiTCEM correction mechanism. A 6-DOF Inertial Measurement Unit (IMU sensor) helps in isolating zero-pressure duration indicating when a foot of the individual is in air during a stride, while obtaining the drift-free static pressure data. The disclosed wearable apparatus calculate the drift-free plantar pressure parameters for long duration and facilitates monitoring walking patterns of the individual.
Abstract:
Techniques for heart rate estimation are disclosed. In an embodiment, synchronized photoplethysmograph (PPG) and 3-axis acceleration signals are received. Further, the PPG and acceleration signals are partitioned into windows. Furthermore, it is determined whether motion is present in a window of the acceleration signal. Moreover, Fourier transform is performed on the signals to obtain power spectra of the signals in the window when there is motion. Also, it is determined whether a peak of the acceleration signal is present in a range around first highest PPG peak. Further, it is determined whether the peak of the acceleration signal affects heart rate of the user when the peak of the acceleration signal is in the range around the highest PPG peak. The heart rate of the user in the window is then estimated using second highest PPG peak when the peak of the acceleration signal affects heart rate of the user.
Abstract:
Currently automobiles use embedded sensors and computational powers for performance optimization. For better performance and maintenance knowing driver and driving style is important. It is known that driver identification can be achieved using dedicated sensors. Since these are external sensors they add to cost and also deployment of many sensors increases operational and maintenance overhead. Embodiments of the present disclosure obtain GPS data including trip information pertaining to a vehicle being driven by a driver and features are extracted from trip information which are ranked by comparing these features with features associated with trip information of other drivers to selectively identify and obtain ranked features. Value of each ranked feature is compared with value of corresponding feature pertaining to driving patterns and an abnormality score for each relevant feature is generated and the driver is authenticated based on the abnormality score.
Abstract:
A computing platform for intelligent development, deployment and management of vehicle telemetry applications is disclosed herein. Further, the present disclosure provides a method and system that enables provision of Intelligent Transportation Service on the Cloud-based Platform that facilitates creation and deployment of vehicle telemetry applications configured for enabling traffic measurements, traffic shaping, vehicle surveillance and other vehicle related services.
Abstract:
The present disclosure envisages a computer implemented system and method for Wi-Fi based indoor localization. The system includes a repository for storing attributes of the floor plan of an indoor area with respect to the zones on the floor plan. A communicating module receives a threshold number of data points from user devices located in the area. These data points include a plurality of Received Signal Strength Indicators (RSSI) captured from the access points positioned in the area. A k-means clustering is then performed on the data points for grouping the data points into ‘k’ number of clusters and a decision tree is built by following a condition based approach. Distance values are then calculated pertaining to the RSSIs stored at the decision tree, and zone circles are plotted. Zone of user presence is then determined by correlating the plotted zone circles upon the floor plan using maximum overlap property.
Abstract:
A physiological parameter measurement device comprising a processor and a video processing module coupled to the processor to divide each of a plurality of frames of a video into a plurality of blocks, where the video is of a body part of a subject whose physiological parameter is to be determined. The video processing module further is to select a block having highest peak signal to noise ratio (PSNR) from amongst the plurality of blocks. Further, the video processing module is to extract a photoplethysmogram (PPG) signal from the video based on a block identifier associated with the block. The physiological parameter measurement device further comprises a signal enhancement module coupled to the processor, to process the PPG signal to obtain an enhanced PPG signal for determining a value of the physiological parameter for the subject.
Abstract:
Disclosed are a device, system and methods for detecting an anomaly associated with driving of a vehicle. Z-axis acceleration data is determined at the device. Based on the Z-axis acceleration data, jerk energies are computed and transmitted to the system for analysis. Further, the jerk energies are received for a plurality of trips at the system. Further, at the system, statistical analysis is performed on the jerk energies for determining a hazard rate for each trip of the plurality of trips. Then based on the hazard rate determined for each of the plurality of trips, a trend analysis is performed. Based on the trend analysis, any anomaly associated with the driving of the vehicle is detected. Further, the anomaly detected may be notified to a person associated with the device or with a monitoring terminal.