Abstract: This disclosure relates to monitoring of machines having one or more vibrating objects. Conventional systems that address the technical problem of detecting frequency of vibrating objects are expensive, require manual intervention, sometimes depend on prior knowledge of location of faults or involve high convergence time. Systems and methods of the present disclosure provide a cost-effective and fully automated solution that employ multiple strobe sources along with a low cost camera. Besides being cost-effective and automated, the solution also reduces convergence time significantly. Employing multiple strobe sources enables generating multiple strobing frequencies in a single iteration. The strobing frequency is a configured to be a multiple of a camera frame rate selected from a set of camera frame rates having mutually prime elements to ensure faster convergence compared to the art.

Abstract: Embodiments of the present disclosure provide systems and methods that establish non-linear components of gyroscope errors which have not been studied or explored earlier. These errors include but are not limited to non-linear dynamic error which is a function of the angular velocity itself. Bias instability has been observed within the same environment of temperature and atmospheric pressure. In other words, the embodiments of the present disclosure analyse and models static bias errors and dynamic non-linear errors in the gyroscope sensor which may be used to model and correct errors accordingly In subsequent measurements. The system provide solution(s) when there is no way of directly estimating temperature for bias correction of gyroscope, by estimating a temperature change by considering indirect measurements from other sensors present onboard the device.

Abstract: This disclosure relates to monitoring of machines having one or more vibrating objects. Conventional systems that address the technical problem of detecting frequency of vibrating objects are expensive, require manual intervention, sometimes depend on prior knowledge of location of faults or involve high convergence time. Systems and methods of the present disclosure provide a cost-effective and fully automated solution that employ multiple strobe sources along with a low cost camera. Besides being cost-effective and automated, the solution also reduces convergence time significantly. Employing multiple strobe sources enables generating multiple strobing frequencies in a single iteration. The strobing frequency is a configured to be a multiple of a camera frame rate selected from a set of camera frame rates having mutually prime elements to ensure faster convergence compared to the art.

Abstract: Energy remains a critical challenge for continuous sensing: with low-capacity batteries, wearable devices require frequent charging. In contrast, installing sensors in everyday ‘smart objects’, such as kitchen cabinets, household appliances and office equipment, supports ADL detection via indirect observations on human interaction with such objects, but cannot provide individual-specific insights in multi-tenanted environments. The embodiments herein provide a method and system for energy efficient activity recognition and behavior analysis. Architecture disclosed utilizes a hybrid mode of inexpensive, battery-free sensing of physical activities performed by a subject been monitored during his Activities for Daily Living (ADLs). The sensing combines object interaction sensing with person-specific wearable sensing to recognize individual activities in smart spaces.

Abstract: Energy remains a critical challenge for continuous sensing: with low-capacity batteries, wearable devices require frequent charging. In contrast, installing sensors in everyday ‘smart objects’, such as kitchen cabinets, household appliances and office equipment, supports ADL detection via indirect observations on human interaction with such objects, but cannot provide individual-specific insights in multi-tenanted environments. The embodiments herein provide a method and system for energy efficient activity recognition and behavior analysis. Architecture disclosed utilizes a hybrid mode of inexpensive, battery-free sensing of physical activities performed by a subject been monitored during his Activities for Daily Living (ADLs). The sensing combines object interaction sensing with person-specific wearable sensing to recognize individual activities in smart spaces.

Abstract: The disclosed embodiments illustrate methods and systems for processing customer data to predict behavioral characteristics of a customer in a physical store. The method includes receiving customer data, pertaining to a shopping episode, of the customer from one or more sensing devices. The method further includes segmenting the shopping episode into one or more segments of time durations. The method further includes categorizing each of the one or more segments of time durations into one of an in-aisle category and a non-aisle category. The method further includes identifying hand-related actions of the customer based on the received customer data. The method further includes determining a likelihood of occurrence of an action-related category based on at least the identified one or more hand-related actions. The method further includes predicting the behavioral characteristics of the customer based on at least the determined likelihood of occurrence of the action-related category.

Abstract: Embodiments of the present disclosure provide systems and methods that establish non-linear components of gyroscope errors which have not been studied or explored earlier. These errors include but are not limited to non-linear dynamic error which is a function of the angular velocity itself. Bias instability has been observed within the same environment of temperature and atmospheric pressure. In other words, the embodiments of the present disclosure analyse and models static bias errors and dynamic non-linear errors in the gyroscope sensor which may be used to model and correct errors accordingly In subsequent measurements. The system provide solution(s) when there is no way of directly estimating temperature for bias correction of gyroscope, by estimating a temperature change by considering indirect measurements from other sensors present onboard the device.

Abstract: The disclosed embodiments illustrate methods and systems for processing customer data to predict behavioral characteristics of a customer in a physical store. The method includes receiving customer data, pertaining to a shopping episode, of the customer from one or more sensing devices. The method further includes segmenting the shopping episode into one or more segments of time durations. The method further includes categorizing each of the one or more segments of time durations into one of an in-aisle category and a non-aisle category. The method further includes identifying hand-related actions of the customer based on the received customer data. The method further includes determining a likelihood of occurrence of an action-related category based on at least the identified one or more hand-related actions. The method further includes predicting the behavioral characteristics of the customer based on at least the determined likelihood of occurrence of the action-related category.

Abstract: Improved descriptive query techniques are provided. More particularly, techniques are provided for specifying and processing descriptive queries for data providers grouped into provider kinds with hierarchical containment relationships. The query may include arbitrary boolean combinations of arbitrary tests on the values of attributes of the data providers.

Abstract: Methods and systems for recommending crowdsourcing tasks. A path traversed by a crowdworker, from one or more crowdworkers, is predicted, based on at least one of a historical data associated with the crowdworker or an input provided received from the crowdworker. The path traversed by the crowdworker comprises a first set of spatiotemporal values associated with the location of the crowdworker. One or more task attributes associated with the one or more crowdsourcing tasks are determined. The one or more task attributes comprise at least one of a second set of spatiotemporal values associated with the one or more crowdsourcing tasks, or rewards associated with the one or more crowdsourcing tasks. A set of crowdsourcing tasks is recommended based on at least the predicted path followed by each of the one or more crowdworkers and the one or more tasks attributes associated with the one or more crowdsourcing tasks.

Abstract: Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.

Abstract: Methods and apparatus of adaptively transmitting data are provided. Data for transmission from one or more incoming data streams is determined in accordance with at least one characteristic of a respective one of the one or more data streams and at least one context external of the data stream. A compression technique for the data and a transmission strategy for the data are modified in accordance with the data determined for transmission.

Abstract: Techniques for selecting a new compression technique or altering the currently instantiated compression technique employed over a data stream in data collection system are provided. At least one change to at least one external contextual condition is detected. One or more modifications to a defined compression technique is generated, either independently or in conjunction with one or more modifications to the event processing operators that operate on the data stream and whose output provides the values that are compressed by the defined compression technique, in response to the at least one change to the at least one external contextual condition. The defined compression technique of the at least one client device is altered in accordance with the one or more modifications to form a modified compression technique through which the unmodified or processed data stream will be compressed before being sent to the server.

Abstract: A method for continually controlling the collective behavior of a set of computing devices in a distributed data processing system. A gateway node disseminates a specification request comprising a set of parameters to a set of computing devices. The gateway node may be unaware of the number and identity of individual computing devices. Each computing node receiving the request determines whether its attributes satisfy the predicates expressed in the specification request. If so, the node processes the parameters in the specification request and modifies its own behavior based on the values in the parameters of the specification request. Subsequently, the gateway node may also observe the quality of information (QoI) values communicated from the set of computing devices. The gateway node iteratively modifies the parameters disseminated in subsequent specification requests based on a divergence between a computed quality of information value and a desired quality of information value.

Abstract: Techniques are disclosed for determining and validating provenance data in such data stream processing systems. For example, a method for processing data associated with a data stream received by a data stream processing system, wherein the system comprises a plurality of processing elements, comprises the following steps. Input data elements and output data elements associated with at least one processing element of the plurality of processing elements are obtained. One or more intervals are computed for the processing element using data representing observations of associations between inputs elements and output elements of the processing element, wherein, for a given one of the intervals, one or more particular input elements contained within the given interval are determined to have contributed to a particular output element. In another method, intervals are specified, and then validated by comparing the specified intervals against intervals computed based on observations.

Abstract: Techniques are disclosed for localized adaptation of client devices based on correlation or learning at a remote server. For example, a method for modifying a behavior of a client device in a data collection system, wherein the client device collects data and transmits data to a server, includes the following steps. The client device transmits data to the server. The server uses at least a portion of the data received from the client device to generate information that represents a modification to a behavior of the client device. The server device transmits the generated information to the client device. The client device subsequently alters the behavior of the client device based on the information received from the server.

Abstract: Improved descriptive query techniques are provided. More particularly, techniques are provided for specifying and processing descriptive queries for data providers grouped into provider kinds with hierarchical containment relationships. The query may include arbitrary boolean combinations of arbitrary tests on the values of attributes of the data providers.

Abstract: Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.

Abstract: Improved descriptive query techniques are provided. More particularly, techniques are provided for specifying and processing descriptive queries for data providers grouped into provider kinds with hierarchical containment relationships. The query may include arbitrary boolean combinations of arbitrary tests on the values of attributes of the data providers.

Abstract: Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.