Driving vivid virtual environments from sensor networks

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 89-95).The rise of ubiquitous sensing enables the harvesting of massive amounts of data from the physical world. This data is often used to drive the behavior of devices, but when presented to users, it is most commonly visualized quantitatively, as graphs and charts. Another approach for the representation of sensor network data presents the data within a rich, virtual environment. This thesis introduces the concept of Resynthesizing Reality through the construction of Doppelmarsh, the virtual counterpart of a real marsh located in Plymouth Massachusetts, where the Responsive Environments Group has deployed and maintained a network of environmental sensors. By freely exploring such environments, users gain a vivid, multi-modal, and experiential perspective into large, multi-dimensional datasets. We present a variety of approaches to manifesting data in "avatar landscape", including landscapes generated off live video, tinting frames in correspondence with temperature, or representing sensor history in the appearance and behavior of animals. The concept of virtual lenses is also introduced, which makes it easy to dynamically switch sensor-to-reality mapping from within virtual environments. In this thesis, we describe the implementation and design of Doppelmarsh, present techniques to visualize sensor data within virtual environments, and discuss potential applications for Resynthesizing Reality.by Don Derek Haddad.S.M

Managing Event-Driven Applications in Heterogeneous Fog Infrastructures

The steady increase in digitalization propelled by the Internet of Things (IoT) has led to a deluge of generated data at unprecedented pace. Thereby, the promise to realize data-driven decision-making is a major innovation driver in a myriad of industries. Based on the widely used event processing paradigm, event-driven applications allow to analyze data in the form of event streams in order to extract relevant information in a timely manner. Most recently, graphical flow-based approaches in no-code event processing systems have been introduced to significantly lower technological entry barriers. This empowers non-technical citizen technologists to create event-driven applications comprised of multiple interconnected event-driven processing services. Still, today’s event-driven applications are focused on centralized cloud deployments that come with inevitable drawbacks, especially in the context of IoT scenarios that require fast results, are limited by the available bandwidth, or are bound by the regulations in terms of privacy and security. Despite recent advances in the area of fog computing which mitigate these shortcomings by extending the cloud and moving certain processing closer to the event source, these approaches are hardly established in existing systems. Inherent fog computing characteristics, especially the heterogeneity of resources alongside novel application management demands, particularly the aspects of geo-distribution and dynamic adaptation, pose challenges that are currently insufficiently addressed and hinder the transition to a next generation of no-code event processing systems. The contributions of this thesis enable citizen technologists to manage event-driven applications in heterogeneous fog infrastructures along the application life cycle. Therefore, an approach for a holistic application management is proposed which abstracts citizen technologists from underlying technicalities. This allows to evolve present event processing systems and advances the democratization of event-driven application management in fog computing. Individual contributions of this thesis are summarized as follows: 1. A model, manifested in a geo-distributed system architecture, to semantically describe characteristics specific to node resources, event-driven applications and their management to blend application-centric and infrastructure-centric realms. 2. Concepts for geo-distributed deployment and operation of event-driven applications alongside strategies for flexible event stream management. 3. A methodology to support the evolution of event-driven applications including methods to dynamically reconfigure, migrate and offload individual event-driven processing services at run-time. The contributions are introduced, applied and evaluated along two scenarios from the manufacturing and logistics domain

Landscapes of ephemeral embrace : a painter's exploration of immersive virtual space as a medium for transforming perception

The following text has been written to illuminate the research embodied In Ephemere, a fullyimmersive virtual environment which integrates stereoscopic 3D computer-generated images and spatialized 3D sound, with a user interface based on breathing, balance, and gaze. This artwork was begun when I entered the doctoral program at CAiNA (Centre of Advanced Inquiry Into the Interactive Arts) in 1997, and was completed in 1998. The work Ephemere is grounded in a very personal vision, developed over more than 25 years of artistic practice, including, most significantly, painting. Ephemere follows on its predecessor Osmose, and as such, Is a continuation of my efforts to: (I) explore and communicate my sensibility of what it means to be embodied, here now, in the living Rowing world; and (ii) use the medium of immersive virtual space to do so, necessarily subverting its culturally-biased conventions to achieve this goal. The contents of this text are most clearly indicated by its title: Landscapes of Ephemeral Embrace: A Painter's Exploration of the Medium of Immersive Virtual Space for Transforming Perception. And further, by its chapter headings: (I) Context: Rethinking Technology in the "Reign of King Logos ; (II) Defining Terms: Key Concepts and Concerns in the Work; (III) Origins of the Work in Prior Artistic Practice: Emergence of Key Concerns and Strategies; (IV) First Explorations in Immersive Virtual Space: Osmose; (V) Continuing Explorations In Immersive Virtual Space: Ephemere; and (VI) Strategies and Their Implications In the Immersive Experience. In this text, I have focused my discussion on artistic Intent, rather than on whether I have been successful, for this can only be evaluated with the passing of time

Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines in Microservice Architectures

Distributed stream processing engines are designed with a focus on scalability to process big data volumes in a continuous manner. We present the Theodolite method for benchmarking the scalability of distributed stream processing engines. Core of this method is the definition of use cases that microservices implementing stream processing have to fulfill. For each use case, our method identifies relevant workload dimensions that might affect the scalability of a use case. We propose to design one benchmark per use case and relevant workload dimension. We present a general benchmarking framework, which can be applied to execute the individual benchmarks for a given use case and workload dimension. Our framework executes an implementation of the use case's dataflow architecture for different workloads of the given dimension and various numbers of processing instances. This way, it identifies how resources demand evolves with increasing workloads. Within the scope of this paper, we present 4 identified use cases, derived from processing Industrial Internet of Things data, and 7 corresponding workload dimensions. We provide implementations of 4 benchmarks with Kafka Streams and Apache Flink as well as an implementation of our benchmarking framework to execute scalability benchmarks in cloud environments. We use both for evaluating the Theodolite method and for benchmarking Kafka Streams' and Flink's scalability for different deployment options.Comment: 28 page

Deep neural networks in the cloud: Review, applications, challenges and research directions

Deep neural networks (DNNs) are currently being deployed as machine learning technology in a wide range of important real-world applications. DNNs consist of a huge number of parameters that require millions of floating-point operations (FLOPs) to be executed both in learning and prediction modes. A more effective method is to implement DNNs in a cloud computing system equipped with centralized servers and data storage sub-systems with high-speed and high-performance computing capabilities. This paper presents an up-to-date survey on current state-of-the-art deployed DNNs for cloud computing. Various DNN complexities associated with different architectures are presented and discussed alongside the necessities of using cloud computing. We also present an extensive overview of different cloud computing platforms for the deployment of DNNs and discuss them in detail. Moreover, DNN applications already deployed in cloud computing systems are reviewed to demonstrate the advantages of using cloud computing for DNNs. The paper emphasizes the challenges of deploying DNNs in cloud computing systems and provides guidance on enhancing current and new deployments.The EGIA project (KK-2022/00119The Consolidated Research Group MATHMODE (IT1456-22

Ag-IoT for crop and environment monitoring: Past, present, and future

CONTEXT: Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task. OBJECTIVE: Ag-IoT systems enable a data pipeline for modern agriculture that includes data collection, transmission, storage, visualization, analysis, and decision-making. This review serves as a technical guide for Ag-IoT system design and development for crop, soil, and microclimate monitoring. METHODS: It highlighted Ag-IoT platforms presented in 115 academic publications between 2011 and 2021 worldwide. These publications were analyzed based on the types of sensors and actuators used, main control boards, types of farming, crops observed, communication technologies and protocols, power supplies, and energy storage used in Ag-IoT platforms

Reconciling the dissonance between Historic Preservation and Virtual Reality through a Place-based Virtual Heritage system.

This study explores a problematic disconnect associated with virtual heritage and the immersive 3D computer modeling of cultural heritage. The products of virtual heritage often fail to adhere to long-standing principles and recent international conventions associated with historic preservation, heritage recording, designation, and interpretation. By drawing upon the geographic concepts of space, landscape, and place, along with advances in Geographic Information Systems, first-person serious games, and head-mounted Virtual Reality platforms this study envisions, designs, implements, and evaluates a virtual heritage system that seeks to reconcile the dissonance between Virtual Reality and historic preservation. Finally, the dissertation examines the contributions and future directions of such a Place-based Virtual Heritage system in human geography and historic preservation planning and interpretation