Stency and Solomon are two of the four children in a single mother parented home that were able to exhibit exceptional abilities to secure education in 2 different private schools that provide a better education away from home problems. At the peak of March, 2020 when schools were closed in Uganda, these 2 underprivileged children lost hope of ever getting to study again. They had no access to educational resources that they could use to keep up with school work. After one and half a year, their schools introduced programs of providing educational materials within their homes that must be fetched by a parent or guardian on a weekly basis and as well be returned back after completion of exercises to get more. The challenge is that the schools are hundreds of kilometers away from their home and their mother being unemployed in this pandemic, has made it difficult to break off from the daily hardships she takes to secure a meal on the table.
There are millions of other children from a family like this whose hopes to acquire education have been shuttered by the pandemic, but to make the matter worse, even after schools creating tentative emergency programs like these where resources are provided within homes to keep up with learning builds another problem of procuring them to the learners homes.
Delivering educational materials in the vicinity of student homes by schools is possible as some students from the same school reside near each other but the main problem has been that data analytics and affordable technological dashboards to easily refine and visualize which students can be found in a particular location adds up to a big procurement and delivery gap worsening the learning crisis.
Nectoroutes is a one stop application that will refine location data of students so as to create centralised delivery plans by schools in the learners' villages and homes. Nectoroutes shall feature artificial intelligence through the IBM Watson Studio algorithms of data refinery to create visualizations and profiles of best centralised localised village spots that schools shall use in order to increase maximum efficiency. This will also help schools to effectively plan how to deliver future lessons based on material availability and delivery logistics to learners in their homes thereby reducing costs of material reception by parents due to delocalisation and decentralization of their location data.
Nectoroutes uses location data to create a centralised points that schools can use to deliver learning resources to learners. The capabilities such as Machine learning, Watson studio and the IBM SPSS Modeler; Nectoroutes adds a value chain of accurate predictions in future demand and resource availability such that schools can ensure resilience and effectiveness while planning for their learners. The distribution chains can be optimised to reduce costs on both the parents and the schools sides and this is also backed up by increasing parents' confidence in the schools and institutions that are working to see that learners have access to learning resources and materials. The intelligent systems ensure a balance and qualitative analysis in resource distribution which is the main challenge affecting many to ensure that all learners have access to equitable and quality education.
Our Model features real World AI techniques from the building process, testing, evaluation and deployment. Artificial Intelligence and Data science are directly and intrinsically linked and this presents to us the time when to best help learners acquire education such that they can be elevated from the vicious cycle of ignorance.
Nectoroutes is a necessity and an important one stop point that will improve educational resource delivery by the schools to the homes of learners with maximum efficiency. This will open opportunities for learners like Stency and Solomon to get started with their education amidst the pandemic where a lot of uncertainty still shadows the official physical schools openings especially in places facing electronic study equipment crisis and unaffordable internet charges.
The visualizations and refined data obtained by the schools can therefore be linked with Nectoroutes Platform which uses centralised locations to ensure delivery of learning resources to particular destinations at low cost. Nectouroutes envisions collaborating with existing delivery service providers such as Uber, safe Boda to link and connect destinations of students. The model of Nectouroutes can easily be scalable as it does not require schools to provide location information of students again but this is obtaineed directly from the cloud and the riders can efficiently deliver multiple school resources for students residing in particular locations. as well, reception of completed packages is easily done as Nectoroutes retraces back the initial directions and centralises the gathered pavkages to be taken back into schools. Nectoroutes shall open doors for unimaginable capabilities especially through connecting routes and destinations amidst the crisis
The pdf attached illustrates the solution flow. A demo version can also be found here NECTOROUTES UI Designs.pdf
Nectoroutes is built with the following
- Node-JS and cloudant
- Object Storage
- IBM Watson Studio
- Kubernetes
- Figma UI
We are still on building and testing stage
The Authors include
- Sheila Nabuduwa_BRAC University
- Aaron Masuba_BRAC University
Nectoroutes is Open Source and Licenced under Apache Licences
We wish to extend our acknowldgements to the following
- IBM Watson and IBM Cloud team
- SAMSUNG
- Call for Code and David Clarck Cause