Synapse Modelers has received the following awards and nominations. Way to go!
Check the written project here.
Check the code foundations here.
CFT – Community Fire Tracker
19th September 2019
Wildfires are becoming a rising problem to the communities and their ecosystems, in fact, each year wildfires are devastating tens of million hectares around the world. Whether controlled, accidental or natural, unhandled forest fires has long-term consequences like threats to human and animal life, deterioration of the health and loss of livelihoods, besides threatens the survival of endangered species, weaken the structure and composition of the ecosystem and provide conditions for entry of invasive species, all of these costing billions of dollars.
The governments are good at reacting to short-term solutions but they lack the tools to offer sustainable solutions on a long-term, indeed science is oversimplified and distorted by politics usually, thus it’s important that people take care of themselves, their environment and play a proactive role preventing, mitigating or supporting the firefighting.
Communications are one of the most valuable elements on a workplace disaster. Precise, timely and relevant information is critical during emergencies, under the risk of imminent conflagrations technology solutions might offer a valuable tool to the people. This project is aiming to empower people and helping them to cooperate and protect themselves.
It’s a Social Bot that is powered by communities, enhanced with Artificial Intelligence (AI) algorithms and supplied with data analysis processed from the open datasets provided by NASA.
Government and Relief agencies will get geo-located facts in real-time provided from whether active users or satellite imagery offered on an open website.
Forecasts based on Data Analysis can be performed using big data techniques. In this way, the conflagration will be prevented, mitigated or attended promptly by both civilians and relief agencies.
When a single user reports a possible fire incident, the bot will trigger alerts to people nearby the threatened place, these people will be notified, able to confirm the fire event, and invited to join a temporal chat group created to host them encouraging cooperation.
False alarms can be managed by the same community as long as they confirm the incident.
On countryside zones equipped with Internet of Things (IoT) infrastructure, people can link their devices to this bot and send reports automatically during fire events, besides if there is no internet available, SMS over GSM/LTE networks can be sent with ease.
Uninhabited zones can be monitored using the forecasts performed by the data analysis along with satellite imagery.
CFT – Community Fire Tracker is a highly scalable solution with small investments, the initial prototype is planned to be developed with Telegram, but it could be easily ported or linked with similar platforms like Whatsapp, Messenger, Signal, and others.
The geo-located reports offer accurate data that communities can leverage with precision to spot the threatened zone.
When the bot receives an atypical report it can dig over other users, trying to confirm the emergent event; this feature is supported by the same community to avoid false alerts. A blockchain approach could be useful on this topic.
Reporting a conflagration emergency is a simple task that is not time-consuming, the users just need to send a text, audio, video or image stream, immediately the bot will propagate the alert notifying users around the reported zone trying to confirm the first report requesting multimedia reports.
Users can get audible instructions that can easily be followed to arrive at safe zones.
Chat apps are ubiquitous on mobile phones, this way the users don’t need to install any extra app that can easily be forgotten or uninstalled when it’s no longer used.
The bot is enabled to receive and process different sort of data that will be analyzed with artificial intelligence to process audio and images mainly.
The bot is capable to get reports from different sorts of devices that can be enabled to automatically send reports through chat messages or SMS.
Making use of Apache Flink API and the NASA’s dataset we are aiming to forecast events to avoid potential conflagrations. This is possible through the analysis of different sources like IoT data streams, community reports, satellite imagery, weather behaviour, terrain characteristics and others.
Develop an open REST API to offer a basic CRUD that will be connected to the bot in its first set up and store the minimal required data. (User ID, Work/Home locations, valuable skills)
Deploy a basic chatbot that is capable of receiving and sending messages to users under a certain ratio around a threatened location.
Integrate Artificial Intelligence in the core of the bot to understand and interpret the content of the messages via audio, image and video mainly as those are the most simple and straightforward ways to send messages during an emergency.
Spread the voice and empower communities with this chat bot. Get registrants and active users via gamification.
Build a framework based on Data Analysis using Apache Flink API to get forecasts based on weather data streams and IoT real-time logged data.
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