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Each time there’s a natural disaster, we see the same scenario: Everyone from national government leaders and the military to the small-town mayor and scores of volunteers with big hearts and expertise come together to respond to the event. All those people, at every level, need to communicate, need to share information and need to coordinate their activities so that they’re doing things efficiently and not duplicating their efforts. And many times, that doesn’t happen effectively because people can’t find or share the information they need, when they need it.
We asked ourselves why – with all the advances in technology like GPS, ubiquitous cell phones and instant communications across so many channels – do disaster relief operations still look like those of 20 or 30 years ago?
Overcoming information overload
Lightship has a field operations platform to help organizations navigate their data to find the necessary information to help them make better, safer decisions. It pulls together all of an organization’s information, such as Geographic Information System (GIS) mapping, drone photos, satellite photos and the real-time locations of people and vehicles.
Of course, putting all that information in one place and giving people access to it is good. But aggregating data is just the start. What often happens is that people become overwhelmed. There’s so much information that they’re supposed to review that they may end up ignoring all of it. We fixed that problem by building filtering systems inside the Lightship platform that sort the information by role and context. Our user-friendly interface lets non-technical users find and employ the information that’s relevant to their specific context or role to make better, faster decisions.
Connecting people with the right information – and with each other
We work with local governments and First Nations communities in Canada, and with several industrial customers in the mining and gas sectors. Our target markets can be complementary, particularly when it comes to disaster relief, because they often need access to the same information. For example, local governments may need to work closely with industrial companies that control critical infrastructure such as power during an emergency.
We designed our system for connectivity. It connects mobile devices, equipment sensors and safety systems. Site managers can see their equipment status and the location of their team members in real time, so that when there’s a problem, the response is quick and intelligent. We started thinking that if it works for individual organizations, we should connect them with each other.
We put this idea to the test during the British Columbia (BC), Canada, fires in 2017. The Lightship Works’ system was being used to help track evacuations, catalogue damage estimates and share information among the non-governmental organizations (NGOs) and government agencies. For example, after a wildfire, families want to get home as quickly as possible, but sometimes it can take a week or more for an agency to give them the all clear because they don’t have all the information they need to make an informed decision. During the BC fire, another agency came to us to see whether our system would work better than the one they were using, which didn’t give them the whole picture of the affected area.
So, field personnel went to the affected area, gathered information and took drone photos and uploaded them to our system. They used our integrated Map application to overlay that information with local-government GIS data about property lines. Quickly, both the agency and the homeowners had a picture of what the ground actually looked like and could make better-informed decisions about when to return and what they would find when they got there.
Adding AI to the information mix
We’ve got the foundational layer for data gathering, and for communicating and filtering that data down to the right people in any given situation. Now we’re working with IBM to see how we can apply AI technology and use some of the rich data IBM can provide so that we can really transform field operations in both the mining and gas sector and for emergency response. For example, we’ve worked with IBM Watson Services and The Weather Company to pilot a solution to predict road hazards for first responders.
We want to apply AI to see how we can help people work smarter and better. We want to see what can we learn about people’s skill sets and locations to be proactive and make suggestions about the tasks they should do, the messages that they need to see and the places that they should go. Instead of having to dig relevant information out of a one-size-fits-all situation report, individuals could self-serve the information that’s going to be the most important for their role on a particular day and for the task that they are working on.
We also want to start integrating and using data from The Weather Company to provide people on the ground with real-time and forecast conditions. For example, if people are going to be fighting a wildfire in a specific area, they can get automatic alerts if the wind is predicted to shift direction or has changed intensity so they can stay out of the way of the moving fire. The Weather Company also has incredible amounts of historical weather data that could help agencies proactively prepare for weather events and natural disasters.
I love the fact that Lightship is building tools that will make a real difference when emergencies happen, and that we’re going to be able to improve outcomes for people. I also feel a tremendous sense of responsibility to get those tools right because they’re going to save lives.
Living in the US Pacific Northwest, we know that there is going to be a large earthquake here someday. And when it happens, Lightship is going to be a part of the recovery. What drives me to constantly strive for a better solution is knowing that the faster that we can get information in context to people, the better the outcome is going to be.
Listen to Jaethan Reichel talk about how IBM is helping Lightship transform the way agencies respond to emergencies: