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World Vision

 3,964

Efficient and Reliable Counting of Improved Latrines

We need a revolutionary advance in the counting of improved latrines in a community or region so it does not require expensive site visits.
stage:
Submission Deadline
prize:
$20,000
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Summary
Timeline
Forum1
Teams7
Summary

Overview

ABSTRACT

The lack of adequate sanitation facilities is a global problem with an estimated 2.3 billion people using unimproved toilets or no toilets at all when eliminating waste. One United Nations Sustainable Development Goal (SDG) is to globally achieve access to adequate and equitable sanitation for all and to end open defecation by the year 2030. World Vision is one of many organizations and governments working towards the achievement of this goal throughout rural low- and middle-income communities but there is a need for efficient and reliable methods to verify and track progress against this goal. World Vision, supported by SeaFreight Labs, is seeking to address this need and the objective of this Challenge is to design a monitoring approach that is optimally cost-efficient, time efficient, reliable and generalizable for rural communities in low- and middle-income countries.

This is a Reduction-to-Practice Challenge that requires written documentation and experimental proof-of-concept data, if available. The Seeker may perform field testing of proposed solutions to determine if they meet the Solution Requirements of the Challenge.

 

OVERVIEW

Openly defecating or using an unimproved toilet is a widespread problem globally leading to significant public health issues with up to 280,000 people dying annually of diarrhea-related causes attributable to poor sanitation. World Vision is working to achieve access to adequate and equitable sanitation for all and to end open defecation by the year 2030 throughout rural low- and middle-income communities. To help measure progress toward this goal, a low-cost, efficient, and reliable method to count the number of improved sanitation facilities in a geographic area is required. Proposed solutions should be able to correctly identify at least 90% of improved toilets in a region while having a very low false positive rate of counting unimproved facilities as improved. Proposals may include and/or combine (1) What data is collected (images, videos, alternative survey questions, etc.), (2) How the data is collected (technological solutions or logistical or process efficiency improvements), (3) When the data is collected (increasing the efficiency of information generated using alternative sample selection or timing coupled with advances in analytical techniques), or (4) Who collects the data (utilizing alternative sources or methods of data generation (e.g., crowdsourcing)) and any other innovative methods to meet the Challenge requirements. Proposals also may require initial setup activities and/or physical placement or inclusion of tags, stickers, or other features to help identify improved latrines.

The submission to the Challenge should include the following:

  1. The detailed description of the proposed solution addressing specific Solution Requirements presented in the Detailed Description of the Challenge. This description should be accompanied by a well-articulated rationale supported by literature/patent precedents.
  2. (Optional) Test results, demonstrations of proposed methods, and/or experimental proof-of-concept data, if available.  

The Challenge award is contingent upon theoretical evaluation and experimental validation of the submitted solutions by the Seeker.

To receive an award, the Solvers will not have to transfer their exclusive IP rights to the Seeker. Instead, Solvers will grant to the Seeker a non-exclusive license to practice their solutions. 

Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on 07-Sep-2021.
Late submissions will not be considered.

 

Visit the challenge at the site of our partner, InnoCentive, at https://innocentive.wazoku.com/#/challenge/b8f56adbc77d41148e33e605e6ecf741?searchIndex=3

 

Timeline
Forum1
Teams7