Showing papers by "Anirban Mondal published in 2014"

Systems and methods for context-aware and personalized access to visualizations of road events

Abstract: The present disclosure is directed to systems and methods for context-aware and personalized access to data corresponding to an event. The data is related to multiple predefined parameters including a location, date, time, and a classifier representing a status or an impact intensity for the event. The method includes receiving the data and an event type for the data. The event type is selected from multiple predefined event types. The method also includes creating a hierarchical data structure configured to spatially index the data based on the selected event type. The hierarchical data structure includes a node representing the selected event type. The node is augmented using a linked list for referring to the data to be stored in a database. The node is associated with a frequency of occurrence of the selected event type.

CityZen: A Cost-Effective City Management System with Incentive-Driven Resident Engagement

Abstract: Cities typically face a wide gamut of management and maintenance problems. Existing automated sensor based solutions are prohibitively expensive to deploy. Furthermore, these solutions need to be complemented by incorporating human judgment for accurate, timely and cost-effective city-related event identification. To this end, this work proposes City Zen, which is a novel platform for event reporting and analytics to engage residents towards city management through incentives. Key contributions include: (a) the City Zen platform with an app for enabling authenticated residents to report events in a city for end-to-end integrated smart city management, (b) Differentiated incentive management based on types and priorities of events, quality and timeliness of event reports as well as resident intent, and (c) a social dashboard for searching events and subscribing for event alerts with additional ability to provide feedback on the event reports. Ongoing pilots and our performance study indicate that the platform indeed performs city management cost-effectively depending on the incentive mechanisms used for engaging residents.

Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model

Abstract: We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a random field (spatial or temporal). The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provide a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. The Karhunen-Loeve expansion is used for dimension reduction of the random field. Furthermore, we use a hierarchical Bayes’ model to inject multiscale data in the modeling framework. In this Bayesian framework, we show that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of MCMC) and are compounded by...

Methods and systems for processing crowd-sensed data

Abstract: The disclosed embodiments illustrate methods and systems for processing crowd-sensed data. The method includes receiving the crowd-sensed data from a mobile device associated with a user. The crowd-sensed data corresponds to metadata of an event pertaining to an aberration in at least one of a public service, a public infrastructure, a private service, or a private infrastructure. Thereafter, the event may be prioritized based at least on a type of the event, a measure of impact of the event, or a measure of urgency to resolve the event. Further, a notification of the event may be transmitted to an organization responsible to at least resolve the event, based on the prioritizing, wherein the notification comprises at least the metadata.

E-VeT: Economic Reward/Penalty-Based System for Vehicular Traffic Management

Abstract: We propose the E-VeT system for efficient vehicular traffic management in road networks using economy-based reward/penalty schemes. In E-VeT, base stations collaboratively facilitate dynamic vehicular route assignments for reducing the traffic congestion, average time of arrival and fuel consumption. The main contributions of this work are two-fold. First, it proposes an R2A (Revenue-based Route Allocation) scheme, which rewards vehicles for following system-assigned longer-time paths, and charges a fee for following system-assigned shorter-time paths. Furthermore, it penalizes vehicles for any deviations from the system-assigned paths. Second, it discusses a route allocation algorithm, which gives lesser-time paths as a preference to vehicles that have earned higher revenue based on the R2A scheme. Preliminary performance study shows that E-VeT is indeed effective in managing vehicular traffic in road networks by reducing the average time of arrival and fuel consumption.

RoadEye: A System for Personalized Retrieval of Dynamic Road Conditions

Abstract: Awareness of dynamically changing road conditions is crucial for a safe and quality driving experience, as well as, in augmenting trip planning. This work addresses the problem of keeping users informed in a timely and personalized manner about road conditions arising from both scheduled and ad hoc events. We propose Road Eye, a system for personalized retrieval of dynamic road conditions. The key contribution of Road Eye is the psi R-tree, which is a novel R-tree-based index augmented with linked lists for facilitating quick and personalized retrieval of user-queried road conditions. Our performance study indicates that the psi R-tree is indeed effective in retrieving dynamic road conditions with reduced query response times and disk I/Os.

Systems and methods for service level agreement focused document workflow management

Abstract: Systems and methods for managing document workflows is disclosed. The method includes configuring and deploying a document workflow based on at least one service level agreement (SLA) parameter. The document workflow includes one or more document processing tasks. The method also includes establishing communication between the configured document workflow and a document management system. The method further includes retrieving a document from the document management system in response to at least one service request received from a first user role. The method furthermore includes accessing the retrieved document to perform the one or more document processing tasks by a second user role. The method also includes generating at least one of a notification and an alert based on statuses of the one or more document processing tasks with respect to the at least one SLA parameter.

Dynamic Content and Route Management in Wireless Networks

Abstract: This is a tutorial paper covering issues associated with dynamic content and route management in wireless networks.

Methods and systems for facilitating document transactions

Abstract: Some embodiments are directed to document banking systems and methods for facilitating service to an account holder. A document banking system includes a receiver for receiving a service request from the account holder and a service point manager for maintaining information about registered service points and service(s) provided by them. The document banking system also includes a location manager for maintaining information about location of the account holder. The system further includes a transaction engine for identifying a service point based on the service request and the location of the account holder; adding document(s) required for processing the service request in a document transfer queue of the service point; generate and provide a reference number to the account holder; and transfer the document(s) to a document account of the service point based on one or more conditions to prompt the service point to provide the service based on the document(s).

Benchmark based performance characterization and scalable design of sensing-as-a-service platform

Abstract: Advancements and proliferation of sensing and actuation technologies in diverse computing and physical devices call for a flexible Sensing-as-a-Service Platform (SeaaS-P) that can enable massive-scale next generation applications. A key aspect of such a platform, which has been largely unexplored in terms of applicability at a massive scale, is the notification system (e.g. city incident notification) to send event alerts to subscribers. Conventional event-based systems (e.g. publish-subscribe) typically trigger notifications with every event arrival. Observations show resources (e.g. CPU) can become bottleneck and get overused when event rates and number of subscriptions go beyond certain thresholds. Thus, it may be necessary to opportunistically delay the notification, i.e. not send the notifications with every event update (e.g., time-triggered periodic notifications), depending on the delay-tolerance of the application. This paper proposes a: (i) benchmark based performance profiling of SeaaS-P in terms of resource utilizations and % notification drop; and (ii) design framework to determine the design boundaries of SeaaS-P notification system for both event-triggered and time-triggered notifications.

CitR: a scalable system for quick spatial retrieval of resident involvement information for smarter cities

Abstract: This paper presents CitR, a scalable system for quick spatial retrieval of resident involvement information.