ETech2008 DisasterTech Robbins Maron 20080305a

The document discusses several potential implications for the next 100 years based on current trends, including: 1) The magnetosphere may weaken in 500 years and no longer protect life on Earth, making plans to leave Earth important. 2) Carbon dioxide levels could reach 1000 ppm, triggering a runaway greenhouse effect that kills planetary life. 3) Future technologies like artificial intelligence and robotics may create synergies but also replace many jobs, requiring a basic guaranteed income. 4) Emerging technologies like nanotechnology, synthetic biology, and artificial intelligence will interact in complex and unpredictable ways that could transform civilization.

Space as a Platform

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It’s a moral and strategic imperative that humanity gets to space, and does so soon. We have a ticking time bomb on our hands, but we don’t know when the clock is going to run out. In short, we are overdue for an extinction-level event. As we’ve dug deeper into the Space Startup market over the 6 months since our original Space as a Platform thesis post in mid-2016, we’ve come to a frightening realization. There are not enough people investing their time nor dollars into the required areas of space to enable us as a species to get there. It’s simply not going to happen, folks.

Lattice Energy LLC - NASA Project Document- Are Investigating LENRs for Power...

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Technologies Changing Industrial Park Requirements and Collective Intelligenc...

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Technologies are changing the requirements for industrial parks and collective intelligence systems can help anticipate future changes. As artificial intelligence, computational sciences, and other emerging technologies converge their capabilities will greatly accelerate progress beyond what any single technology can achieve alone based on Moore's law. This will change what is possible and require new thinking about the future of work, economics, and how industrial parks can support tenants through consulting, maker hubs, industrial ecology networks, and collective intelligence systems.

Artificial learning machine intelligence

The document discusses artificial intelligence and machine learning. It notes that unstructured data accounts for 90% of enterprise data and explores why this time is different for AI. It then outlines Google's machine learning spectrum and some of their projects using AI like Global Fishing Watch and Project Wing to save energy and deliver goods via drones. It concludes by thanking the audience and discussing teaching computers like babies for the future of AI.

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This document provides background information on solar power, including definitions of key terms like photovoltaic and suggestions for evaluating the credibility of websites. It lists various sources of information on solar power, such as National Geographic, government documents, and trade associations. It also notes tools for analyzing points of view and determining the credibility of online sources.

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OpenRelief is a project developing communication tools for disaster relief using unmanned aerial vehicles (UAVs) and sensors to map affected areas and gather critical information. The first step was creating a fixed-wing UAV using off-the-shelf components like an autopilot, camera, and sensors running open-source software. While the software is easily hackable, integrating hardware and developing specialized airframes remains challenging. OpenRelief aims to work with groups worldwide to improve UAV and sensor technology for disaster response.

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Crisis Commons is a global network of volunteers who use technology to help communities during crises. They organize CrisisCamps where volunteers come together to develop and improve crisis response tools. Crisis Commons was founded in 2009 and helped respond to crises like the 2010 Haiti earthquake by coordinating volunteers through various technologies and tools. CrisisCamp Ireland aims to establish volunteers in Ireland to help with crisis response and preparedness.

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Understanding OpenRelief

OpenRelief is developing unmanned aerial vehicles and sensor modules to gather information in disaster zones to help relief efforts. Their first project is a flexible robotic plane that can take off from small areas, map landscapes, and measure conditions using modular sensors. The goal is for these open source tools to provide critical data to existing disaster management platforms to help get aid to those who need it most.

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This document discusses how technology can help with disaster response and humanitarian aid. It outlines a pattern of 1) a disaster occurring, 2) initial ad-hoc adaptations using available tools, 3) a champion emerging to advance the technology, and 4) iterative improvements. Examples include using GPS and Google Maps after Hurricane Katrina, and crowdsourcing image analysis through Amazon Mechanical Turk for search and rescue efforts. It emphasizes the need to work with non-profits, understand their needs, get direct experience in disaster response, and become champions for technologies that can truly make a difference for humanitarian organizations.

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Web 4.0’s scale and social impact surpass by several orders of magnitude the inception of its 1.0 ancestor 25 years ago. Web 4.0 will change how humans operate and the way civilization functions. A few specific nanotechnologies, developed at a faster-than-anticipated pace, mostly outside the conventional silicon-based industry circuits, are quickly colliding into the foundations for web 4.0. The Big Picture on Nano details this ‘Coming-of-Ages’, provides a preliminary springboard to grasp context, challenges and opportunities that will accompany this web 4.0 wave of changes, and explains why massive social, economic and geopolitical displacements can be expected.

CASA UASSC Meeting May 2016- Presentation by Industry Chair, Terry Martin

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This is the presentation given by Dr Terry Martin at the CASA UASSC in May 2016. He is the current Industry Chair. Note that the original presentation contains extensive animation. In order to maintain the animation effect, the presentation has been split into individual slides however this now makes it more than 270 slides. This may be offputting to some! Please note that the contents are the view of Dr Martin and are not necessarily endorsed by CASA. The presentation covers 5 key areas: Part 1: (Slides 1-65) Covers some innovative UAV applications such as NASA UTM, and Google Loon, before discussing the impact of automation on the jobs market, internationally and Nationally. The key point is that disruption and automation mean that many jobs are at risks, and Australia could be vulnerable if it continues on its current path Part 2 (Slides 67-82) then provides an overview of the recently amended RPAS regulatory framework Part 3 (Slides 83- 171 ) then works through whats broken in the current RPAS UASSC before describing the efforts of Europe and the US, the implications of Australian having no UAV Roadmap, the need for a pragmatic appreciation of our national capacity, particularly when it comes to the expertise necessary to making assessments about risk, safety and equipage requirements. Part 4 (172 - 243 ) Selected elements of Detect and Avoid and Command and Non Payload Communications are outlined Part 5 (244- 286) proposed steps we could take to identify our priorities, identify the operational and technical shortcomings that are hindering UAV integration and work with Industry more effectively to achieve that end state. This includes the restructure plans for the UASSC Working Groups.

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NASA's Center of Excellence for Collaborative Innovation (CoECI) educates the NASA workforce on crowdsourcing and challenges. It makes these tools easy to use by reducing barriers. CoECI has completed over 333 challenges on topics like software, algorithms, design, and more. Challenges provide significant cost savings over traditional contracts, often 40% on average. CoECI also helps manage the challenge pipeline and implements lightweight processes to promote adoption of open innovation across NASA.

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This document summarizes a presentation about using multimedia technologies for emergency situations. It discusses: 1) The potential of emerging multimedia technologies like smartphones and social media to help with disaster response and management by providing real-time situation reports and coordinating relief efforts. 2) Prototype applications that have been developed like one for the Thai floods that used flood level and shelter data along with tweets to help direct aid. 3) Remaining research challenges around issues like human reporting of data, real-time situation recognition from multiple data streams, and predictive analytics. 4) The vision of building a global "situation map" by analyzing the billions of photos uploaded from smartphones to help recognize situations worldwide.

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In this document, we will refer to a generalized and broader use case of AIML and IoT into Disaster Response scenarios. Watch this live session on Youtube: https://www.youtube.com/watch?v=pgZDsGBzJuE&t=1414s This guest talk at the IIT-Guwahati zoom-live session on the launch of the 2022 Batch of AIML certification, addressed the questions like; How AIML is helping this world to be a safer planet for a living? How humans have become intelligent over years by using Artificial Intelligence and Machine Learning to handle Disasters? How the wildfire in technologically advanced countries is getting handled or maturing to get ready to handle? How big is this disaster problem? How drones are helping to fight disasters? Connect with me at: http://abhilashshukla.com/ For download. kindly Mention/DM me on LinkedIn or Twitter: https://www.linkedin.com/in/abhilashshuklaa/ https://twitter.com/AbhilashShuklaa

University of florida 3 d lapidary scanner 110614

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The subject invention pertains to an apparatus and method for collecting 2-D data slices of a specimen. Embodiments can incorporate a lapidary platen and an image recording system to image a specimen. The lapidary wheel platen can provide an imaging plane such that an image can be taken as the lapidary wheel platen abrades a surface of the specimen. A specimen mount can maintain the surface of the specimen properly aligned in the image plane. The imaging system can be a continuous recording system such as a video camera, a discrete recording system such as a flatbed scanner, or combinations of continuous and discrete recording systems to simultaneously collect two distinct data sets. The 2-D data set(s) can then be processed to create intricate 3-D color models.

Four Disruptive Trends for the Next Decade

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Four disruptive trends will shape the next decade: 1) Distributed software systems will drive disintermediation and disrupt industries like transportation and hospitality; 2) Networked virtual reality will allow for planetary-scale collaboration and remote viewing; 3) Climate change will require adaptation of infrastructure to become intelligent, secure, low-carbon and climate-resilient; 4) Brain-inspired computing utilizing massive data and exascale supercomputers will enable emulation of the human brain within a decade and usher in an era of cognitive technologies.

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An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowdsourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real- world datasets.

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