Autonomous Ground Robot Helps Firefighters in Enclosed Spaces

Note the number of integrated sensors

Autonomous Ground Robot Helps Firefighters in Enclosed Spaces

Interesting Engineering

By Nergis Firtina, February 21, 2023

Researchers at Spain's Universidad Rey Juan Carlos and Universidad Autónoma de Madrid developed an autonomous ground robot to help firefighters plan safe access routes to affected areas of a building and assist with evacuations. The robot is equipped with sensors to collect temperature, humidity, and air quality data and to identify its position and those of other objects. That data is stored in a database accessible through a smartphone app. Researcher Noelia Fernández Talavera said the robot’s evacuation mode "uses the prior knowledge of the scene to compute the shortest path from the current position to the target one. This target position can be the exit of the building or the location of a victim, among other things." ... ' 

AI Supports Displaced Peoples, Refugees in Ukraine and Beyond

Impressive depth of applications.  Good examples to consider for the future. 

AI Supports Displaced Peoples, Refugees in Ukraine and Beyond

By Karen Emslie

Commissioned by CACM Staff, September 15, 2022

The United Nations (U.N.) reported in May there were around 7.7 million internally displaced persons (IDPs) in Ukraine, people who have been forced to leave their homes but who remain in the country. Meanwhile, the U.N. High Commissioner for Refugees (UNHCR, the U.N. refugee agency) recorded over 5.9 million Ukrainian refugees who have fled their country to locations across Europe.

The humanitarian crisis in Ukraine is part of a global situation in which over 89 million people worldwide were found to be "forcibly displaced" due to persecution, conflict, violence, or human rights violations at the end of 2021, according to UNHCR.

Displaced peoples and refugees face a multitude of difficulties, from poor living conditions and loss of identity documents to longer-term resettlement, discrimination, and employability issues. Researchers and technology companies have been working with relief organizations, non-governmental organizations (NGOs), and governments to develop solutions, some of which are based upon artificial intelligence (AI), to support IDPs and refugees worldwide.

Ukraine: Responding to the immediate crisis

Palo Alto, CA-based Orbital Insight is using AI and geospatial data to monitor the movements of displaced peoples and refugees in Ukraine. The observations support agencies involved in the relief effort— including the U.S. Department of State and the U.S. Agency for International Development (USAid)—to deploy aid and emergency resources where and when they are needed.

Orbital Insight operates a cloud-based platform that uses data including vehicle,  foot-traffic, and land-use observations to provide insights on global economic, societal, and environmental trends. Its clients typically come from sectors like defense and intelligence, energy, and financial services.

The platform's raw data is obtained from multiple sources. It includes high-resolution electro-optical (EO) satellite imagery (which includes information from beyond the visible spectrum) supplied by satellite manufacturer and operator Satellogic, as well as data from connected vehicle sensors and anonymized geolocation sensors on mobile devices. Customized algorithms are used to analyze the data and perform specific tasks, like computer vision-based classification and object detection.

When war broke out in Ukraine, Orbital Insight CEO Kevin O'Brien and his team adapted the platform's capabilities to the conflict. Foot-traffic algorithms, for example, can track the volume, direction, and speed of displaced peoples' movements. The company's analysis showed how foot traffic dropped off dramatically in eastern Ukraine as people fled intense fighting in the region—  and how it then grew in cities in the west of the country as displaced peoples moved to those safer areas.

Such insights support humanitarian organizations' decision-making, such as whether emergency shelters and food should be redeployed to areas that people are moving towards. "Some of the first use-cases were to help manage relief resources both in Ukraine and at border locations," explained O'Brien. "The next was safe exit, safe passage: how do you get people further away from the fighting?"

Satellite imagery gives an aerial view of the situation at borders as refugees cross into neighboring countries like Poland and Moldova. Computer vision provides further insights by automatically counting the number of vehicles at border crossings. The results can be downloaded as geoJSON files, loaded onto a Geographic Information System (GIS), and visualized on maps for further analysis by relief organizations.

Alongside contracts with governmental agencies, Orbital Insight donates analytics via the Data Partnership, a collaborative platform that allows tech companies to share data with international development organizations for research and humanitarian purposes. The company also works directly with partners in Ukraine, including with Reface, a Kyiv-based AI startup that developed a popular face-swapping app and content creation platform. Reface has redirected its focus towards the conflict via numerous initiatives, including developing algorithms to identify Russian troops in satellite imagery and using data to fight disinformation.  ...   (more detail) 

Karen Emslie is a location-independent freelance journalist and essayist. 

Simpler Desalinization for Disaster

 Did a survey of desalinization methods in college.  Likely best for disaster relief.

A PORTABLE DESALINATION SYSTEM MAKES WATER POTABLE—WITHOUT A FILTER

By Payal Dhar (Freelance Blogger)

MIT researchers have developed a prototype of a suitcase-size device that can turn seawater into safe drinking water.

According to the International Desalination Association, more than 300 million people around the world now get their drinking water from the sea. With climate change exacerbating water scarcity globally, seawater desalination is stepping in to fill the void. But whereas commercial desalination plants are designed to meet large-scale demand, there is also a need for portable systems that can be carried into remote regions or set up as stand-ins for municipal water works in the wake of a disaster.

A group of scientists from MIT has developed just such a portable desalination unit; it’s the size of a medium suitcase and weighs less than 10 kilograms. The unit’s one-button operation requires no technical knowledge. What’s more, it has a completely filter-free design. Unlike existing portable desalination systems based on reverse osmosis, the MIT team’s prototype does not need any high-pressure pumping or maintenance by technicians.

The MIT researchers described their invention in a paper titled “Portable Seawater Desalination System for Generating Drinkable Water in Remote Locations.” The paper was posted in the 14 April online edition of Environmental Science & Technology, a publication of the American Chemical Society.

The unit uses produces 0.3 liters of potable drinking water per hour, while consuming a minuscule 9 watt-hours of energy. Plant-scale reverse-osmosis water-treatment operations may be three to four times as energy efficient, and yield far greater quantities of freshwater at much faster rates, but the researchers say the trade-off in terms of weight and size makes their invention the first and only entrant in a new desalination niche.

The most notable feature of the unit is its unfiltered design. A filter is a barrier that catches the impurities you don’t want in your water, explains Jongyoon Han, an electrical and biological engineer, and lead author of the study. “We don’t have that specifically because it always tends to clog, and [then] you need to replace it.” This makes traditional portable systems challenging for laypeople to use. Instead, the researchers use ion-concentration polarization (ICP) and electrodialysis (ED) to separate the salt from the water.

“Instead of filtering, we are nudging the contaminants [in this case, salt] away from the water,” Han says. This portable unit, he adds, is a good demonstration of the effectiveness of ICP desalination technology. “It is quite different from other technologies, in the sense that I can remove both large particles and solids all together.” .... ' 

Testing the Meaning of Digital Darkness

Perhaps a good case study to understand the implications of complete digital darkness, how should we address this and what are the capabilities that need to be provided, in what order. 

Tonga Faces Weeks of Digital Darkness

By The New York Times, January 20, 2022

As in many remote Pacific nations, the island kingdom of Tonga is connected to the world by a single cable, roughly the width of a garden hose, that carries hair-thin optic fibers across a vast ocean bed.

That lone conduit is the means by which Siniva Filise, who lives in Wales and is part of the large Tongan diaspora, starts each day with a video call from her mother 10,000 miles away. "She's like the alarm — she doesn't care what time it is," Ms. Filise said. "She'll just call."

But for the past four days, the phone has been silent. Tonga's undersea cable was severed by a huge volcanic eruption on Saturday night, and the country now faces weeks of digital darkness as a repair ship prepares to make its way from Papua New Guinea.

A repair ship is not expected to reach Tonga until Feb. 1, after a voyage of more than eight days. Then it will perform the difficult task of retrieving two sections of damaged cable from the ocean floor and splicing in replacements, with the threat of fu

View Full Article   

Removing Rubble with Robots

What robots can be taught to do.

 Faster Path Planning for Rubble-Roving Robots

University of Michigan News, August 13, 2021

A new algorithm designed by University of Michigan (U-M) scientists could enhance the performance of robots traversing treacherous terrain. The algorithm can accelerate path planning for robots that use arm-like appendages to maintain balance on rough ground like disaster areas or construction sites. U-M's Yu-Chi Lin said, "First, we used machine learning to train the robot on the different ways it can place its hands and feet to maintain balance and make progress. Then, when placed in a new, complex environment, the robot can use what it learned to determine how traversable a path is, allowing it to find a path to the goal much faster." In a virtual experiment, a humanoid robot using the new algorithm outperformed previous methods in negotiating a corridor of rubble..... 

Military Digitization

 An approach to military digitization, also for peace time efforts of crisis management and disaster recovery. 

German Armed Forces Order Deployable Mission-Critical Communication Networks from Motorola Solutions to Drive Greater Digitization  in BusinessWire

Contract value of the framework agreement is worth 254 million euros.

CHICAGO--(BUSINESS WIRE)--Digitization is one of the highest priorities for the German Armed Forces. It will help to increase efficiency of operations and safety for soldiers and civilian personnel. Secure and reliable voice communications as well as access to data are central drivers for efficiency and responsiveness on any successful mission.

Cross-agency communication is also a prerequisite for successful cooperation between different teams, particularly in the event of a crisis or disaster. As part of the digitization of land-based operations and to ensure fast communication in various areas in the field, the German Armed Forces (Bundeswehr) are procuring deployable communication networks, which are available in two versions, mobile and stationary. The modernization marks an important milestone within the Bundeswehr's military’s digitization strategy.... "

AI and Machine Learning for Disaster Cost Estimation

AI and Natural Disaster Cost Estimation.   The kind of problem that is greatly expanding. 

Artificial Intelligence and Machine Learning Are Important Tools to Improve Cost Estimation for Natural Disasters in Electric Utilities  by Ismael Arciniegas Rueda and Parousia Rockstroh

December 4, 2020

Natural disasters in the United States cause billions of dollars of damage to electric infrastructure every year. Hurricane Zeta, for instance, left more than 2 million people without power in the Gulf States. According to the Quadrennial Energy Review by the Department of Energy, electric system outages caused by natural disasters have an economic cost of $20-$50 billion annually.

After a disaster hits a particular area, states rely heavily on the Federal Emergency Management Agency (FEMA) to fund a significant portion of repairs. But FEMA's responsiveness to affected communities depends on its ability to estimate the costs of this work quickly and accurately.

The normal procedure to approve and allocate funding requires an extensive cost estimation process—one that is particularly difficult for electric infrastructure work that can require specialized workers and equipment. In the context of natural disaster recovery, this estimating work is rife with uncertainties (and, of late, made even more difficult because of COVID-19). For instance, in Puerto Rico after Hurricane Maria, significant electric repairs needed to be performed in hard-to-reach mountainous areas, demanding helicopters with highly trained work crews. At the same time, electric infrastructure repair is critical and urgent—other repair work can't go on without it.  .... "'

Thinking Assistive Disaster AI

A clear example of the interactions of sensors, logic, decisions and leveraging experience.  Some general ideas of the possibilities.

Assistive AI in Decreasing Natural Disaster Damage

Assistive AI is an invaluable tool to minimize the damages of natural disasters.  By Jack Williams  in SmartDataCollective

 A few years ago, we talked about the benefits of using AI and big data in disaster relief. We have recently seen how important these applications are, as the damage of natural disasters is worse than ever.

Mother Nature has been busier than ever this year, with natural disasters adding to the stress of the COVID-19 pandemic. A number of hurricanes have wreaked havoc on the Gulf Coast, and wildfires recently devastated the West Coast. Unfortunately, these severe weather events now occur more frequently. In seven of the last 10 years, there have been 10 or more weather-related disasters with costs exceeding $1 billion each. Among the 115 costly catastrophes since 2010 were so-called “1,000-year floods,” Category 5 hurricanes, and the most massive wildfires in history.

These problems put the importance of big data and AI to the test, as we strive to fight the problems they cause.

Worsening Disasters Highlight the Need for New Assistive AI Solutions

The problem is that, despite their calamitous effects, many natural disasters can be surprisingly difficult to spot in their beginning stages. For example, the 2018 Camp Fire in California that tore through large portions of the state, eventually burning over 150,000 acres and destroying more than 18,000 structures, began in the blink of an eye; it spread over the first seven miles in less than 90 minutes.  ... " 

Boston Dynamics Helping Chernobyl Decommission

 Boston Dynamics is doing quite well with its mostly telepresence Spot Robotics.  Here another example, with apparent connection to specialized sensors. 

Boston Dynamics' Spot Is Helping Chernobyl Move Towards Safe Decommissioning

Legged robots are uniquely qualified for sensing around what's left of Chernobyl's Reactor   By Evan Ackerman in IEEE Spectrum

In terms of places where you absolutely want a robot to go instead of you, what remains of the utterly destroyed Chernobyl Reactor 4 should be very near the top of your list. The reactor, which suffered a catastrophic meltdown in 1986, has been covered up in almost every way possible in an effort to keep its nuclear core contained. But eventually, that nuclear material is going to have to be dealt with somehow, and in order to do that, it’s important to understand which bits of it are just really bad, and which bits are the actual worst. And this is where Spot is stepping in to help.    ... 

More:  https://chnpp.gov.ua/en/infocenter/news/5668-boston-dynamics-robot-at-chnpp

Fighting Disasters with AI

We connected with PNNL, an impressive group.

DOE Announces ‘First Five Consortium’ to Fight Natural Disasters with AI
Oliver Peckham in Datanami

As wildland fires tear across California and hurricane season starts to warm up, natural disasters are top-of-mind for many Americans. Predicting and managing these disasters is an ongoing challenge, and researchers are leveraging technology from supercomputing to big data analytics to try to bridge these gaps. Now, the Department of Energy (DOE) has announced the First Five Consortium: a group of leaders in the AI space determined to use intelligent tools to combat natural disasters in the United States.

The consortium, co-chaired by the DOE and Microsoft, was formed in response to a January White House forum focused on disaster responses and is named after the “critical first five minutes in responding to a disaster.” The areas it hopes to tackle include wildfire prediction and fire line containment; damage assessment; search and rescue; and natural disasters like hurricanes and tornadoes.

In support of the consortium, Microsoft has established a “critical infrastructure team” that will use AI, confidential computing, advanced communications and more to improve disaster resilience.

“Artificial intelligence enables us to address some of humanity’s greatest challenges, and in this case, improve disaster resilience for populations around the world,” said Toni Townes-Whitley, president of U.S. regulated industries for Microsoft. “As evidenced by this consortium we have joined with the DOE and [the Department of Defense], it’s critical that private and public sectors work together to provide first responders with technology that has the potential to save lives.”

As an example project, the DOE highlighted ongoing work from Pacific Northwest National Laboratory (PNNL) and the Joint Artificial Intelligence Center (JAIC) in the Department of Defense (DoD). The researchers are scaling a prototype that uses deep learning algorithms to provide close-to-real-time data for first responders.  ... " 

Loon for Disaster Response

Recently mentioned some updates on Project Loon Balloons, some updates for disaster response"

Loon partners with AT&T to ready internet balloons for disasters globally
Providing emergency internet in times of crisis
By Jon Porter@JonPorty  May 6, 2020, 9:00am EDT ... " in TheVerge

Cloud Based Reactions to Natural Disasters

Basic idea is good,  support the system with useful and readily available knowledge to support operations.  Probably harder though to actually make decisions based on quality of data available.

Cloud-Based Electronic System May Help First Responders Better React to Natural Disasters
Purdue University News
By Chris Adam

Purdue University researchers have developed a cloud-based supply chain management system to help emergency responders track inventory and distribution in countries hit by natural disasters. Purdue's Yuehwern Yih and colleagues worked with first responders to understand their requirements when responding to areas struck by catastrophic events; the system is designed to replace paper forms and ad hoc spreadsheets often used in developing nations to track vital resources. Data can be entered offline for syncing to the system through Wi-Fi or network connections, and the full life cycle of items in the system can be traced. Yih said, "The Purdue system can provide real-time data to allow better tracking of supplies and aid so that help reaches those most in need."  ... '

Drones for Disaster Relief

Here looking at how drones can react and recover from disaster disruptions to provide ongoing support.

Could Nearly Invincible Drone Be the Future of Disaster Relief?
USC Viterbi News
By Caitlin Dawson

At the University of Southern California Viterbi School of Engineering, researchers have developed autonomous drones that can recover from collisions and other disruptions. Using reinforcement learning to train the controller that stabilizes the drones in simulation mode, the researchers presented randomized challenges to the controller until it learned to navigate them. The researchers tested the controller by subjecting them to disruptions like kicking and pushing; the drones were able to recover 90% of the time. Viterbi’s Gaurav Sukhatme said the research resolves two important issues in robotics: robustness (“if you’re building a flight control system, it can’t be brittle and fall apart when something goes wrong”), and generalization (“sometimes you might build a very safe system, but it will be very specialized”). ... ' 

Boston Dynamics Spot Robot Dog Goes on Sale

You can now sign up for one of the Boston Dynamics Spot Robot Dogs,  still in the early adopter program.  Not really publicly available,  but Boston Dynamics will work with you to design specific applications.

A kind of semi-autonomous dog-like robot, that works in many kinds of terrain, with lots of videos of it online.  approximate cost of one is said to be about the cost of a luxury car.   Very impressive operations, but also creepy and borderline scary.   Probably not consumer facing.   But for security and disaster recovery? Video below outlines many specs:



Here in IEEE Spectrum:

Boston Dynamics' Spot Robot Dog Goes on Sale
Here's everything we know about Boston Dynamics' first commercial robot    By Erico Guizzo

Boston Dynamics is announcing this morning that Spot, its versatile quadruped robot, is now for sale. The machine’s animal-like behavior regularly electrifies crowds at tech conferences, and like other Boston Dynamics’ robots, Spot is a YouTube sensation whose videos amass millions of views.

Now anyone interested in buying a Spot—or a pack of them—can go to the company’s website and submit an order form. But don’t pull out your credit card just yet. Spot may cost as much as a luxury car, and it is not really available to consumers. The initial sale, described as an “early adopter program,” is targeting businesses. Boston Dynamics wants to find customers in select industries and help them deploy Spots in real-world scenarios.  ...   " 

Considerable detail, about potential uses and competitors in this article ...

Fujitsu Models and Predicts with Learning

Have met with Fujitsu and was impressed with their analytics work. Also has direct connections to very high powered computing.  At first this looked more like a classical simulation analytics approach, but can see how some learning techniques can be integrated into the problem to focus prediction.  In fact any classical analytical techniques would benefit from a means that learns over time to adapt to varying goals and contexts.   So then everything can be tagged as learning  'AI'.  So a good example for that kind of a problem?  Worth a further look.

AI disaster mitigation technology to predict river flooding with limited data   by Fujitsu in Techxplore. 

Fujitsu today announced the development of a technology that draws on mathematical models built with limited data on rainfall and water levels to create flooding predictions for rivers. The solution leverages Fujitsu Human Centric AI Zinrai, a comprehensive portfolio that encompasses Fujitsu's wide range of AI technologies and techniques, and utilizes a model that incorporates insights from hydrology to produce an AI that achieves predictions with greater precision.

The new technology proves effective even for smaller rivers with limited measurement data or for areas where water level sensors have been newly installed and have yet to accumulate sufficient data. These predictions will offer authorities a vital tool for delivering faster response times and mitigating flood damage in the event of a natural disaster, including in dispatching personnel to affected areas and supporting appropriate decision-making in issuing evacuation advisories.

Fujitsu and Fujitsu Laboratories will continue to work to further perfect this technology through a field trial with local governments across Japan with the aim of delivering a commercial solution during fiscal 2019. With the development of this solution, Fujitsu demonstrates how this and other AI technologies will play an important role in bolstering its efforts to combat the effects of climate change, and contribute to the achievement of greater sustainability in society. ....  "

Merck Drone Medicine Delivery in Puerto Rico

Drones move forward for advanced delivery tasks in disasters  Some intriguing details are included.

Merck takes part in test of medicine-delivery drones in Puerto Rico
Merck, Volans-I, Softbox and AT&T are working with Direct Relief to test the drone system, which will deliver medicines to remote areas of the island.    By  Alaric Dearment in MedCityNews

As the devastation wrought by Hurricane Maria in Puerto Rico becomes clearer, one of the largest drugmakers in the country is participating in a test of a drone system designed to deliver medicines to areas affected by disasters.

Merck & Co. – together with Softbox Systems, Volans-I, AT&T and the nonprofit group Direct Relief – began piloting the test of emergency medical supply deliveries on the island last week. The drones carry medicines to which people often lose access in disasters and include temperature-controlled units that can carry products requiring refrigeration. Volans-i manufactures the long-range drones, while Softbox makes the packaging system for transporting cold-chain medications.  .... " 

Network for Natural Disasters

Good idea, when will it move further, though also polluting.

IBM-Backed Project Creates Wi-Fi Network For Natural Disasters in SupplychainBrain

From a cramped living room in Brooklyn, New York, a handful of young computer nerds has developed a new way to use technology to help save lives in natural disasters.

They have designed tiny electronic nodes inside baseball-sized rubber casings that create a special Wi-Fi network spanning more than 100 square miles that can be used to connect victims and first responders. It’s a simple and relatively cheap concept, but during a natural disaster when cell towers topple, technology fails and entire communities fall into darkness — communication can be the difference between life and death.

The five young men met competing against each other at computer hackathons. They joined together to compete in a contest sponsored by International Business Machines Corp. last year called Call for Code, which asked developers to use cloud, artificial intelligence and other technologies to amplify preparedness for natural disasters. Their entry, Project Owl, which stands for Organization, Whereabouts, and Logistics, uses a “clusterduck” network made of hubs that resemble rubber ducks, which can float in flooded areas. Once deployed, civilians are able to get on their cellphone to connect with first responders. Emergency workers are also able to learn about weather and get information data analytics through the cloud. .... "

Human Presence Sensing for Smart Buildings

In  RDMag.

NSF Grant Awarded for Smart-building Sensor Research  by University of Hawai’i

The National Science Foundation has awarded University of Hawaiʻi at Mānoa researchers a $750,000 grant to develop a low-cost sensor capable of detecting human presence and monitoring occupants for energy-savings and smart-building applications. The Small Business Technology Transfer (STTR) Phase II grant was awarded to UH Mānoa in partnership with technology company Adnoviv.

Olga Borić-Lubecke, professor of electrical engineering in the College of Engineering and a co-principal investigator on the grant, co-founded Adnoviv in 2013 with electrical engineering Professor Victor Lubecke. The company focuses on research-driven technology, developing innovative sensors and systems for industrial, medical and security applications, including its centerpiece product, True Presence Occupancy Detection Sensors (TruePODS). Adnoviv is a Phase I graduate of the XLR8UH start-up program and has already hired four UH graduates. ... "

Can AI Fix Disaster Relief?

Visuals are interesting here in the linked article below.  Another example of where there needs to be strong, real-time collaboration with human interactions.

Disaster Relief Is Dangerously Broken. Can AI Fix It? 
By Katharine Schwab in FastCompany

The use of artificial intelligence in disaster relief is gaining favor as weather-related catastrophes grow in frequency and severity. For example, a startup founded by Stanford University's Ahmad Wani has launched a machine learning platform to help cities respond to floods with specialized maps that update in real time so emergency crews can determine where aid is most needed. Wani said a key challenge was enabling rapid, city-wide analysis of structural engineering to better predict damage. The Flood Concern risk map was based on an earlier algorithm that digests building construction and retrofitting data, integrated with information on building materials and surrounding soil properties, to predict earthquake damage. Flood Concern crunches vast data volumes based on water-flow physics, previous flood data, and satellite imagery to approximate water depth, direction, and speed and localize areas at most risk; demographic data is layered atop the prediction so emergency planners can anticipate areas with the most likely at-risk residents. .... " 

Rubber Duckies for Disaster

Clever idea, disposable drop-in sensors being used to creat networks, understand and communicate ad-hoc in disaster conditions:

IBM is funding a fleet of rubber ducky-inspired gadgets to help disaster response   In Fast Company

The classic rubber ducky has many attributes. It’s cute, tough, and super buoyant. For one team of coders, those kid-friendly, bath-time qualities inspired something more: a disaster response startup that just won $200,000 and the chance for worldwide implementation through IBM’s inaugural Call for Code competition. Project Owl–an acronym that stands for “organization, whereabouts, and logistics”–will air-drop (likely via drone) their plucky “Clusterduck” armada into a disaster area ... 

The devices are small, hexagonal rubber balls that are waterproof, durable, and house mini-Wi-Fi relays, which can work together to create an ad hoc mobile network.

Each individual “ducklink” has a transmission range of about 400 meters. These signals overlap and connect to “Mamaducks,” larger long-range, low-power transmitters that knit all that coverage together. Smartphone and laptop users who join the Project Owl network will receive a pop-up allowing them to report to rescue workers their location, condition, and make clear what exactly they need to survive (that’s about as much data as the limited network will allow).

The data the network collects can then be used to create a dashboard that will allow first responders to better understand the scope of any scenario. This IBM Cloud-based system relies heavily on IBM’s Watson Studio and related Cloud APIs, along with data from the Weather Company, its forecasting service. When combined, the idea is to map and display many aspects of devastation, from where group resources might already be deployed, to ongoing and projected weather patterns. .... "