crowdsourcing

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course. A proof-of-principle study

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options.

ViFi: virtual fingerprinting WiFi-based indoor positioning via multi-wall multi-floor propagation model

Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such issue: crowdsourcing and RSS radiomap prediction, based on either interpolation or propagation channel model fitting from a small set of measurements. RSS prediction promises better positioning accuracy when compared to crowdsourcing, but no systematic analysis of the impact of system parameters on positioning accuracy is available.

Improving road safety knowledge in Africa through crowdsourcing. The African Road Safety Observatory

Africa is the worst performing continent in road safety: the fatality rate, 26.6 per 100.000 inhabitants, is almost three times that of Europe's and fatalities per capita are projected to double from 2015 to 2030 (WHO, 2015). This is mainly due to the fact that Emerging Economies are experiencing increases in traffic, for which their traffic systems are not sufficiently prepared. On one hand, there is a significant demand for data and knowledge to be used for road safety-related decision making.

Road safety issues addressed by Africa Road Safety Plan: Are still relevant?

In 2011 the Africa Road Safety Action Plan (ARSAP) established an Action Plan to meet the objective of reducing road traffic crashes by 50% by the year 2020. Despite this effort, the situation worsens year after year and Africa is the continent with the worst road safety performance. To contribute reverse this trend, the SaferAfrica project, a joint effort of 17 partners from Africa and Europe, was launched in 2016. Within the framework of SaferAfrica project, the Crowdsourcing tool was developed and implemented through the African Road Safety Observatory.

© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma