Abstract: This disclosure relates generally to method and system for detecting on-street parking violations. The method include capturing, by using an media capturing device embodied in an electronic device mounted in a vehicle, a video stream of a scene during a trip of the vehicle. The video stream is processed at the electronic device to identify target objects such as no-parking signage and vehicles parked in the vicinity thereof. A meta-information associated with the target objects is stored in form of a short-term historian in a repository associated with the electronic device. The absolute locations of the target objects are determined and the historian is updated with the values of the absolute locations. A set of unique target objects is determined from amongst the target objects and a meta-information associated with the unique objects is sent to a cloud server for determining parking violations.

Abstract: This disclosure relates generally to method and system for providing assistance to interviewers. Technical interviewing is immensely important for enterprise but requires significant domain expertise and investment of time. The present disclosure aids assists interviewers with a framework via an interview assistant bot. The method initiates an interview session for a job description by selecting a set of qualified candidates resume to be interviewed. Further, the IA bot recommends each interviewer with a set of question and reference answer pairs prior initiating the interview. At each interview step, the IA bot records interview history and recommends interviewer with the revised set of questions. Further, an assessment score is determined for the candidate using the reference answer extracted from a resource corpus. Additionally, statistics about the interview process is generated, such as number and nature of questions asked, and its variation across to identify outliers for corrective actions.

Abstract: Vehicle-to-Grid (V2G) technologies are being adopted to reduce peak demand and to take over as energy sources during grid instability. It is necessary to estimate attributes of electric vehicle trips and residual battery charge in order to correctly predict spatio-temporal availability of energy from EVs to form a micro grid. However, it may not be feasible to get the required attributes for all vehicles in a city-scale traffic scenario. Embodiments of the present disclosure and system address the problem of accurately estimating the local energy reserve that is available from parked EVs during a given time of the day. In addition, the system also determines which neighborhoods have the potential to form micro grids using the parked EVs during a given time period. This will help grid operator(s) to plan and design smart grids which can create EV-powered micro grids in neighborhoods during periods of peak demand or during disruptions.

Abstract: Traditionally, benchmarking of asset performance involves comparing actual performance with ideal values that correspond to test conditions which may not be realized in practice leading to inappropriate ranking of the assets. Systems and methods of the present disclosure use condition-aware reference curves for estimating the maximum possible operating efficiencies (under specific operating conditions) instead of the theoretical maximum efficiencies. The reference curves are received from the manufacturer or obtained from on-site test results. Benchmarking is then performed based on two dimensions, viz., an inter-asset metric and an intra-asset metric that are analogous to the first law and second law of thermodynamics respectively. The two-dimensional benchmarking then helps in identifying inefficient assets that may be analyzed further for finding the root cause.

Abstract: Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.

Abstract: The present disclosure provides a method and a system for estimating capacity and usage pattern of behind-the-meter energy storage in electric networks. Conventional techniques on estimating an effective capacity of behind-the-meter energy storage of a consumer, in presence of distributed energy generation units is limited, computationally intensive and provide inaccurate prediction. The present disclosure provides an accurate estimate of the effective capacity and usage pattern of behind-the-meter energy storage of a target consumer utilizing data samples received from a utility in presence of one or more distributed energy generation units, using an energy balance equation with less computation and accurate prediction. Based on accurate estimation of the effective capacity and usage pattern, the utility may plan for proper infrastructure to meet power demands of the consumers.

Abstract: A system and method for predicting travel time of a vehicle on routes of unbounded length within arterial roads. It collects historical information from probe vehicles positions using GPS technology in a periodic fashion and the sequence of links traversed between successive position measurements. Further, it collects information of neighborhood structure for each link within the arterial roads network. Any of the existing conditional probability distribution functions could be used to capture the spatio-temporal dependencies between each link of the arterial network and its neighbors. It learns the parameters of this data driven probabilistic model from historical information of probe vehicle trajectories traversed within the arterial roads network using an associated expectation maximization method.

Abstract: Accurate estimation of the trajectory of a vehicle by selecting optimal number of GPS data points and a shortest path technique applied for estimation is important and crucial. Method and system for estimating a trajectory from GPS data points is described. The method disclosed utilizes a plurality of GPS data points of a vehicle, an existing road map and a set of equal time intervals obtained by dividing an elapsed time during movement of the vehicle. Each GPS data point is associated to a time interval and a set of candidate points are mapped to each GPS data point correspondingly. A set of possible paths are determined between the set of candidate points in each time interval to estimate the trajectory of the vehicle using one of a shortest path technique and an edit distance technique.

Abstract: Electrical utilities offer incentives to customers to reduce consumption during periods of demand-supply mismatch. A building's participation in demand response (DR) depends both on its ability (due to building constraints), and its willingness (a function of incentive) to reduce electricity. Customers prefer a large incentive whereas a utility would want to minimize the revenue outflow to achieve a target reduction. Systems and methods of the present disclosure identify optimal incentive from the utility's perspective reflecting this trade-off. A model is built to estimate the demand response potential (DRP) of a building for a given incentive offered by the utility. The models for individual buildings are used to characterize the behavior of an ensemble of buildings. The utility may then decide optimum incentives that should be offered to achieve a target DR, using the associated DRP.

Abstract: The present disclosure provides system and method for determining optimal decision parameters for a demand response (DR) event involving a District Cooling Plant (DCP). Most of conventional DR event techniques address control of building-level energy consumption loads alone while in presence of District Cooling (DC) has not received much attention when a plurality of buildings are served by a District Cooling Plant (DCP). The disclosed system and method determine set points of optimal decision parameters of the plurality of buildings and the DCP, by conditioning and un-conditioning on the DCP parameters such that a thermal discomfort of occupants residing in the plurality of buildings is minimum and achieves a maximum target energy demand reduction during the DR event. The disclosed system and method work for hundreds of buildings and able to determine the optimal decision parameters for each building and the DCP efficiently.

Abstract: Identifying policy violations for controlling behavior of an Internet of Things (IoT) automation system is provided. Traditional systems and methods provide for controlling IoT based automation system based upon a static analysis of a system model and rules. The embodiments of the proposed disclosure provide for controlling behavior of the IoT automation system by identifying one or more policy violations, wherein the one or more policy violations are identified by generating a plurality of models representing behavior, relationships and functions of one or more sub-systems corresponding to the IoT automation system; extracting a set of modelled rules; constructing, using each of the plurality of models and the set of modelled rules, an integrated model; and identifying, from the integrated model, the one or more policy violations via a Model Verifier Component for controlling behavior of the IoT automation system.

Abstract: Accurate estimation of the trajectory of a vehicle by selecting optimal number of GPS data points and a shortest path technique applied for estimation is important and crucial. Method and system for estimating a trajectory from GPS data points is described. The method disclosed utilizes a plurality of GPS data points of a vehicle, an existing road map and a set of equal time intervals obtained by dividing an elapsed time during movement of the vehicle. Each GPS data point is associated to a time interval and a set of candidate points are mapped to each GPS data point correspondingly. A set of possible paths are determined between the set of candidate points in each time interval to estimate the trajectory of the vehicle using one of a shortest path technique and an edit distance technique.

Abstract: This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.

Abstract: Method and system for predicting temporal-spatial distribution of load demand on an electric grid due to a plurality of Electric Vehicles (EVs) is described. The method includes creating an EV load demand (EVLD) model for a Region of Interest (ROI) serviced by the electric grid, wherein the EVLD model integrates an EV model and a transport simulator simulating EV traffic conditions for the ROI. Further, the method includes computing the load demand in time and space in terms of State of Charge (SOC) of a battery for each EV among the plurality of EVs in the ROI, based on the EVLD model. Furthermore, the method includes aggregating the computed the load demand, in terms of the SOC, of each EV in time domain and space domain to create a temporal-spatial impact of the load demand by the plurality of EVs on the electric grid for the ROI.

Abstract: This disclosure relates generally to method and system for detecting on-street parking violations. The method include capturing, by using an media capturing device embodied in an electronic device mounted in a vehicle, a video stream of a scene during a trip of the vehicle. The video stream is processed at the electronic device to identify target objects such as no-parking signage and vehicles parked in the vicinity thereof. A meta-information associated with the target objects is stored in form of a short-term historian in a repository associated with the electronic device. The absolute locations of the target objects are determined and the historian is updated with the values of the absolute locations. A set of unique target objects is determined from amongst the target objects and a meta-information associated with the unique objects is sent to a cloud server for determining parking violations.

Abstract: The present disclosure provides a method and a system for estimating capacity and usage pattern of behind-the-meter energy storage in electric networks. Conventional techniques on estimating an effective capacity of behind-the-meter energy storage of a consumer, in presence of distributed energy generation units is limited, computationally intensive and provide inaccurate prediction. The present disclosure provides an accurate estimate of the effective capacity and usage pattern of behind-the-meter energy storage of a target consumer utilizing data samples received from a utility in presence of one or more distributed energy generation units, using an energy balance equation with less computation and accurate prediction. Based on accurate estimation of the effective capacity and usage pattern, the utility may plan for proper infrastructure to meet power demands of the consumers.

Abstract: The present disclosure provides system and method for determining optimal decision parameters for a demand response (DR) event involving a District Cooling Plant (DCP). Most of conventional DR event techniques address control of building-level energy consumption loads alone while in presence of District Cooling (DC) has not received much attention when a plurality of buildings are served by a District Cooling Plant (DCP). The disclosed system and method determine set points of optimal decision parameters of the plurality of buildings and the DCP, by conditioning and un-conditioning on the DCP parameters such that a thermal discomfort of occupants residing in the plurality of buildings is minimum and achieves a maximum target energy demand reduction during the DR event. The disclosed system and method work for hundreds of buildings and able to determine the optimal decision parameters for each building and the DCP efficiently.

Abstract: Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.

Abstract: Disclosed is a system and method for optimizing cooling efficiency of a data center is disclosed. The system may comprise an importing module, a Computational fluid dynamics (CFD) modeling module, a scope determination module, a metrics computation module, an identification module and a recommendation module. The importing module may be configured to import data associated to the data center. The CFD modeling module may be configured to leverage an external CFD Analysis tool in order to develop a CFD model of the data center. The scope determination module may be configured to determine a scope for optimizing the cooling efficiency of the data center. The metrics computation module may be configured to compute metrics based upon the data. The identification module may be configured to identify inefficiency and a cause producing the inefficiency. The recommendation module may be configured to facilitate optimizing cooling efficiency of the data center.

Abstract: A system and method for predicting travel time of a vehicle on one or more routes within arterial roads. It collects historical information from probe vehicles positions using GPS technology in a periodic fashion and the sequence of links traversed between successive position measurements. Further, it collects information of neighborhood structure for each link within the arterial roads network. A NoisyOR conditional probability distribution function is proposed to capture the spatio-temporal dependencies between each link of the arterial network and its neighbors. It learns the parameters of this data driven probabilistic model from collected historical information of probe vehicle trajectories traversed within the arterial roads network using a proposed expectation maximization method.