@article{MAKHILLAJIT201615226507,
    title = {A Location-Based Framework for Mobile Blood Donation and Consumption
Assessment Using Big Data Analytics},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {22},
    pages = {4475-4481},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.4475.4481},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.4475.4481},
    author = {Sherin},
    keywords = {Big data analytics,large scale time series regression analysis,prediction,blood donation,blood donor app,location-based services,mobile computing},
    abstract = {Recently, the advancements in communication technology accompanied by the widespread
availability of mobile devices have greatly evolved mobile health care applications. Blood donation systems
are one of the crucial management systems in health sector, where instant responses to immediate needs for
specific blood group in case of emergencies is vital. Thus, the fulfillment of blood demands in the right time
from the nearest blood banks draws a necessity to efficiently direct donors to the right location to donate.
In this study, we propose a Location-based Analyzer for Mobile Blood Donation Assessment (LAMBDA)
framework. The proposed framework uses large-scale time series regression analysis techniques to analyze
blood demands and donations matching data initiated from a mobile application and forecast blood
shortages and wastages per blood group for a specific location. Accordingly, donors can be directed to the
nearest location having shortage of their blood group. Hence, blood wastage rates are improved
dramatically.}
    }