Flood Identification as a Service - FIaaS

Empowering you to help the world around you.

Governments worldwide are concerned with climate threats and recognize the need for more enhanced natural environment monitoring systems, can  predict hazard occurrences, provide an indication of its scale,and assist in mitigating potential losses (Tkachenko et al 2017 ).Within the Caribbean region, there is a void of acceptable practices to assist planning stakeholders such as engineers and planners to prepare for and alleviate the effects of flooding within the region (Lumbroso et al 2011) . However, Cloud technologies as a tool to process large amounts of data for flood analysis may be a solution to this apparent dilemma. Cloud technologies can be described as providing a service to multiple tenants on demand with ubiquitous network access (internet), easily scalable where tenants pay per usage (IBM 2015). 

Hughes et al (2006) stated that traditional flood monitoring approaches inherently create a scenario where there is a separation between the on-site sensors used to collect data, and the off-site computational grid required to analyze the collected data. This approach makes real-time flood monitoring fundamentally unachievable as there would be a lag in data collection to data analysis. Additionally, traditional sensors become and logistically and financially impractical, as they only collect information at a particular nodes along the floodplain. Hydrologists traditional approach to flood prediction has been to deploy depth and flow-rate sensors at various sites that are prone to flooding (Hughes et al 2006). To produce real-time flood warnings, and monitoring there should be more on-site ‘intelligence’ is required.

User generated content (UGC) publicly shared through social media platforms, is becoming a useful source of data for analyses requiring real-time insights into human behaviour (Tkachenko et al 2017). This now provides more on-site intelligence for a flood identification and monitoring system. Tkachenko et al (2017) explained that applications of UGC in the context of flood monitoring have targeted the use of timestamps and location metadata to ascertain useful knowledge about hazard development. Therefore, according to Tkachenko et al (2017),  UGC  can provide a more robust geographical coverage of the hazard as opposed to the traditional sensor networks. Tkachenko et al (2017), also identified that  UGC provides documentation of personal observations and experiences, as the impact of a hazard on the spatial extent is recorded.

FIaaS is a solution to the need for an acceptable GIS practice using social media to identify and thereby monitor  coastal flooding across Trinidad and Tobago. It presents a method for using social media as input data to produce a Web - based GIS that illustrates the incidents of flooding in Trinidad and Tobago real-time. The methodology allows for real time processing by utilizing cloud technologies to transfer and store data to the GIS. This method has been identified to be more useful than traditional methods of flood monitoring and early warning techniques.

FIaaS presents a method for using social media as input data to produce a Web - based GIS that illustrates the incidents of flooding in Trinidad and Tobago real-time. The methodology allows for real time processing by utilizing cloud technologies to transfer and store data to the GIS. This method has been identified as more useful than traditional methods of flood monitoring and early warning techniques. It can also be used to gather data on trends and move towards trend analysis and preditions of coastal flooding.This is a new application of existing technology (social media analytics).

Social Media as a technology is perhaps the most critical aspect to the solution. The Twitter API is the main data acquisition tool to report how the coastal communities are affected. Also, The website that illustrates the reports also interfaces with mapping APIs to have the tweets displayed.

The Goal is to assist the early response and disaster preparation agencies in the Caribbean as the Hurricane season approaches by giving them a spatial 'web of sight' of how the coastal communities are being affected real-time.

My vision is to create a space within the Caribbean Territories where data driven decision making  becomes a part of the culture. I have and intend to continue to meet with NGOs, Disaster preparedness & Environmental Authorities to show how technology and data can allow for effective policy making, enforcement and implementation. Social media campaigns, engaging local media houses and ICT roadshows are the main methods for reaching the masses to let them know about the solution and its benefits. 

The beneficiaries of the the solution is the public at large and the customers would be the agencies that require the information for immediate response and/or deployment of resources. I intend to reach my customers primarily through ICT roadshows by partnering with the Caribbean Telecommunication Union. However, the beneficiaries would be targeted through social media campaigns. 

The solution is in a pilot phase, serving 30 persons.

The bot engages the user for information on floods that may be affecting them in their communities. They respond through tweets, volunteering information such as the location of the event (latitude & longitude), Video and/or pictures and a description (The text of the tweet). The bot now gives them site of how others are affected through the website, those creating a community of 'reporters'.

I expect to see a spike in the population of users as the hurricane season approaches in a matter of weeks. It will allow them to effectively share the impacts of the coastal communities real -time allowing for faster responses by the relevant authorities.

In three years I see the solution being more than coastal impacts or flooding but a tool to report on any hazard affecting any community. 

Problem Solving, effective communication, networking, marketing, coding, team leadership, project management.

FIaaS will be sustained through 'tenants' of the service. This means that each agency from each region has their own account with data specific to them. As we expand in various territories, we expand our tenants. Also, as we expand in the type of hazards that can be reported there is also the potential for new tenants. These tenants pay a monthly fee for access to the data and illustrations.

Solve can be a platform that can exponentially increase the visibility of my solution that can attract potential clients, investors and partners.

The key barrier is establishing contact with partners. Solve and bridge this gap with the relationships that it already possesses.