Finalist : Sparrow Platform

Sparrow is an open-source AI-enabled platform that serves as a one-stop enabler of medical and psychological well-being during and after disasters. For users, Sparrow uses conversational AI and is easily accessible through a chat app. Sparrow acts as the user’s single point of connection with all applications, communication platforms, doctors, and more during and after a disaster.

See the key services Sparrow used in their solution:

Cloud Foundry → Cloud Functions →

malnou

One of the lingering effects from droughts is malnutrition, particularly in children. Project malnou is a low-cost IoT device that can enable efficient digital tracking of BMI, protein percentage, body fat percentage, and other health related data in drought-affected children. An SMS-based communication system has also been set up using Watson NLU so that the parents can log and track the status of their child’s recovery.

See the key services Project malnou used in their solution:

Watson Natural Language Understanding → Watson IoT Platform → Cloudant →

Regional Winner: Purva-Suchak

Project Purva-Suchak aims to prevent the pervasive flooding that plagues the Indian subcontinent. By continuously checking reservoirs, dams and bodies of water, Project Purva-Suchak can collate data with weather forecast information. This allows them to generate effective flood prediction data that can be stored on blockchain and accessed by those who need the data most including government agencies and disaster management teams. Up to date and accessible data can prevent flooding and huge losses of life and property.

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See the key services Purva-Suchak used in their solution:

Watson IoT Platform → Blockchain → Twilio →

Rx Pharmacist

Project Rx Pharmacist uses a smartphone app to track and catalogue donated medications so that the right medication can be easily found by medical and rescue volunteers. By using IBM Cognos, the app uses visual recognition to identify the medication, and an IoT device to sort it. The app ensures that the right person gets the right medicine in a timely fashion.

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See the key services Rx Pharmacist used in their solution:

Watson Machine Learning → Visual Recognition →

Advancers.ai

Advancers.ai is working to address the growing malaria problem in developing nations. Advancers.ai is an automated, fast, and reliable diagnosis system using image recognition and an attachable microscope that gives accurate counts of infected blood cells with 96% accuracy. This solution ensures early detection and treatment for affected individuals.

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See the key services Advancers.ai used in their solution:

Watson Machine Learning → Visual Recognition →

Global Winner: Prometeo

There are no individualized strategies and polices to protect firefighters from the cumulative effect of smoke and toxic substances that are inhaled. Prometeo is a cognitive platform where sensors from firefighters’ uniforms collect data and send it to a Cloudant database for professionals to monitor their health in real time.

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See the key services Prometeo used in their solution:

Kubernetes Cluster → Node-RED → Watson Machine Learning →

Voluntree

Voluntree is a mobile cross-platform application that facilitates peer-to-peer communication and collaboration in case of natural disasters. Push notifications alert and connect people affected by catastrophes with volunteers who have the ability to help in an efficient and reliable way.

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See the key services Project malnou used in their solution:

Push Notifications →

The R-IO Suite

The R-IO Suite platform is dedicated to support a crisis management approach, in improving preparation and response phases. Data is collected by sensors of potentially affected lands and people and interpreted to create a model on a geographical information system so that it is easily visualized.

See the key services R-IO Suite used in their solution:

Cloud Foundry →

Deep Learning: SEER

Project Deep Learning: SEER developed a system of near-real-time monitoring and predicting forest and grass fires based on satellite observations and powered by Deep Learning models. The models provide distinct fire coordinates, estimating the fire frequency in the vicinity for users to view fire information in their region.

See the key services SEER used in their solution:

Machine Learning → Weather Company Data →

Finalist : AsTeR

In a disaster, 911 call centers are overwhelmed and lack resources for the sudden uptick in calls. Project AsTer prioritizes the calls in order of emergency level, where callers leave a brief explanation, which are converted from speech to text and are analyzed in real time. AsTer also offers a visual map to quickly identify areas and the amount of people affected.

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See the key services SEER used in their solution:

Cloud Foundry Python apps → Natural Language Understanding → Speech to Text →

Regional Winner: Code Nova

Cellular networks often go down in natural disasters, making it difficult to carry out transactions that use mobile payment solutions. Code Nova enables person-to-person mobile transactions for people to purchase the things they need locally with their smartphones. Once reconnected to cellular service, the transactions are confirmed by their bank and will go through.

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See the key services Code Nova used in their solution:

Kubernetes Cluster → Node-RED → Watson Machine Learning →

postdisaster-handler

postdisaster-handler is a system to set first responders on the safest, fastest, and most helpful paths. Using satellite imaging, drone footage, and visual recognition, maps guide first responders to where they need to go – as safely and efficiently as possible. Adjustments are made in real time as new obstacles arise, guiding around sharp objects, exposed wires, and more potential hazards.

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See the key services postdisaster-handler used in their solution:

Visual Recognition → Machine Learning →

QRP-Eden

Many elderly people live alone, with nobody looking after them. In the case of an emergency, this can be extremely dangerous for them. QRP-Eden developed an IoT wearable device worn by the elderly where health data, including heart rate and blood pressure, are monitored regularly. This data would be stored on the blockchain and in case of an abnormality or emergency, help would be sent out to assist them.

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See the key services QRP-Eden used in their solution:

IBM Kubernetes → IBM Database for Redis → IBM Compose for MySQL →

Spark Program

The Spark Program utilizes a bank and Watson Studio to create personas for victims of a natural disaster, where they would be automatically adjusted to create a reasonable loan quota. When a disaster does strike, people can apply for this little-to-no-interest loan to rebuild their lives. The Spark Program also enables donations and donation matching by the bank.

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See the key services Spark used in their solution:

IBM Node.js SDK → Watson Studio →

The Global Aid Match System

The Global Aid Match System is an app for governments, organizations, and civilians to request assistance after a natural disaster. The program matches the person or entity with the best individual or group to help them. The use of blockchain allows for transparency of information and enables all participants to be aware of areas that need the most assistance and areas where assistance is no longer needed.

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See the key services Global Aid Match used in their solution:

Blockchain → IBM Cloud →

Prevent the Outbreak of Infection

Using Watson Visual Recognition, Project Prevent the Outbreak of Infection has a database with images of bacteria to help staff at shelters where victims are forced to reside. The images help workers identify infectious bacteria before an outbreak can commence. All of this data would be public so that experts can comment and validate the diagnoses.

See the key services Prevent the Outbreak of Infection used in their solution:

Visual Recognition → IBM Cloud Object Storage → IBM Cloud IaaS Virtual Server →

Regional Winner: KOUDOU Flow

With universities in mind, Project KOUDOU Flow establishes flow-based planning networks to maximize safety. Their system makes it easier to create and follow along with disaster plans, so that when disaster strikes, everyone in the vicinity knows what the next step is. IoT devices are also used to derive building integrity and to get a headcount on who is okay and who needs help so that nobody gets left behind.

See the key services KOUDOU used in their solution:

Node-RED Starter → Watson IoT Platform → Watson Text to Speech →

Blooming – Everybody Smiles More

When disaster strikes, there are many people who volunteer to help those in need. However, before volunteers can assist, they spend a large amount of time on day-of learning and dispersal. These processes can be done ahead of time online. Project Blooming’s main goal is to establish the most efficient way to digitize this whole process and store data by using a Cloudant database. In doing so, volunteers can maximize their efforts to actually help people and those in need will get help as soon as possible.

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See the key services Blooming used in their solution:

Node-RED → Watson Personal Insights → Watson Natural Language Classifier →

Regional Winner: CALMH (Collaboration Assessment and Learning for Mental Health)

Project CALMH is a platform where users access educational tools to prevent mental health impairments, and guidance in the wake of disaster. Powered by the IBM Cloud Cognos Dashboard, the platform also connects a community of volunteers worldwide with psychiatric training to help those impacted.

See the key services CALMH used in their solution:

Liberty → Node.js → API Connect →

DopplerDrone

DopplerDrone sends in a preliminary drone to impacted areas to map the terrain and obtain information on what medical or other supplies are needed most quickly with the help of the IoT Platform. A second drone flies into the zones with supply crates filled with what is needed most. This system significantly cuts down on response time for those who need help fast.

See the key services DopplerDrone used in their solution:

Cloud Foundry → Cloudant DB → Watson Studio →

Project Rex

Using blockchain technology, Project Rex is trying to bring transparency to charity, by registering all movements related to donations. Blockchain removes the risk of duplicate entries or fraud and provides transparency on where donations go. This system creates a ledger of exactly what is needed and where so that communities can get the resources they need efficiently and with clarity.

See the key services Project Rex used in their solution:

Blockchain →

Antenna S.O.S. Emergency System

When disaster strikes, power and communications are the first to go. Antenna S.O.S seeks to fix this problem with a localized network with chat and data recording functions, so that communities affected by natural disasters can still help each other while waiting for outside assistance. All of the data is sent to IBM Cloud for public use.

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See the key services Antenna S.O.S. used in their solution:

IBM Cloud → Cloudant →

Mi Rio

Flooding is without a doubt one of the most deadly and economically costly natural disasters. Project Mi Rio uses data from The Weather Channel, mathematical models, and accessible content. Combining data that is already out there with new data, communities are able to see the risk level in their area. Interactive maps on smartphones informs when conditions are worsening and flooding is likely.

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See the key services Mi Rio used in their solution:

Watson Assistant → Speech to Text → Weather Channel →

Alpha

After a natural disaster, there is a huge need for blood donors. With Alpha, donors and recipients track specific donations, from where it began all the way to where it ends up. Alpha also provides some details on available information on the donor’s blood and sends an SMS message thanking the donor when the blood has been used.

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See the key services Alpha used in their solution:

Blockchain → PHP Cloud Foundry → Cloudant →

DR Box

Using a network of interconnected drones, DR Box takes images and videos of post-disaster landscapes. This data is then used to decide what locations need medical assistance or supplies. DR Box operates on the model of a fully automated fleet of supply drones as opposed to manually controlled drones.

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See the key services DR Box used in their solution:

Java Microservice with Spring → Push Notifications → Weather Company Data →

Cantalopa

Project Cantalopa aims to conserve and optimize water usage in times of drought by developing a points system through a website and mobile app. The residents’ water meters are tied to their profile and are awarded points if they keep water consumption below a certain level. Residents can cash in on rewards for their good habits with things like vouchers and discounts.

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See the key services Catalopa used in their solution:

MongoDB → IBM Node.js SDK →

Regional Winner:Smart Irrigation System

A key factor behind droughts is poor water use by the large agricultural community. The Smart Irrigation System puts an IoT device in every farmer’s field to detect moisture levels in the soil. The device informs exactly when and how much water the crops need. The device also contains machine learning models to detect new crop types and wilting.

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See the key services Smart Irrigation System used in their solution:

Watson Studio → IBM Cloud →

FREE Sensor

The FREE Sensor is designed to monitor CO exposure in first responders. Data collected from sensors worn by responders is sent to a dashboard, where support teams can make safer deployment decisions based on CO exposure to individual crew members.

See the key services FREE Sensor used in their solution:

Watson Studio → Cloudant → Cognos Dashboard →

Finalist : Healios

Healios provides accessible, high-quality mental health care for victims of natural disasters, by streamlining the process for case workers to connect with survivors who may be coping with negative mental health symptoms. By leveraging the IBM Watson platform, Healios can provide high-quality mental health care at scale by way of a mobile application, compatible with both iOS and Android, and acts as a chatbot for ease of use.

See the key services Healios used in their solution:

Watch the video

Watson Assistant → Natural Langugage Understanding → Watson Speech to Text →

SAFER

SAFER leverages a suite of powerful hardware and software tools to enhance early warning systems, improve situational awareness, and streamline response efforts to get help to those that need it most. Incorporating drones, Project SAFER displays the precise location of blocked roads, damaged infrastructure, and missing persons in near-real time through a dynamic map with the help of IBM IoT services and visual recognition.

See the key services SAFER used in their solution:

Redis → Node-RED → Machine learning →

Finalist : Rove

Project Rove is a chatbot through SMS where victims can give information on their status, health, and more. The chatbot analyzes each status with Natural Language Understanding and generates priority scores for victims. The scores are visualized on a dashboard, helping responders get a view on which areas need the most help. Rove also aids rescue workers by identifying buildings or roads that are severely damaged and noted as risks.

See the key services ROVE used in their solution:

Cloud Foundry → Watson Studio → Natural Language Understanding →

Zephyrus

Before natural disasters occur, Project Zephyrus’s sensors measure the size of each raindrop/hailstone to measure accumulation that can predict soil erosion. If large hail is detected, Zephyrus alerts users downwind to cover their cars and valuables. The sensor is sensitive enough to pick up vibrations from thunder and even gunshots and could be used to track their occurrences, helping rescue workers.

See the key services Zephyrus used in their solution:

Cloudant → Watson IoT Platform → Node-RED →