Big Data is ‘key to reducing food waste’
By Carly Yuk
Food waste has always been a global issue. Growing costs and legislation aimed at reducing the problem is inspiring businesses to use big data in order to tackle the issue.
The inaccurate forecasting of increasing consumer demand, which can lead to huge piles of wasted food, can be improved by examining waste streams and defining an ‘optimum inventory level’.
The United Nations has stated that approximately one-third of food produced worldwide is wasted – some nations, including Italy and France, have made compulsory that food retailers must donate the food rather than throw it away.
The report states that data should be checked on stores and locations that create the highest wastage levels, which upsurges costs to the companies and infringes upon legislation for dealing with food wastage.
With this data, it can be used to fine-tune supply accordingly to these locations. A continuous monitoring and analysing of this data, tweaking for differing demands and seasonal trends, can improve a company’s waste management issues.
Can data cure cancer?
Researchers pursuing the cure for cancer are getting a huge enhancement from big data. Healthcare analytics is predicted to grow to $24 billion in 2021 thanks to innovative hospitals that are using big data to forecast falls and prioritise patients.
Arizona State University is undergoing a research project that observes millions of spots in human DNA to detect cancer-causing variations.
Using Apache Hadoop, the open-source programming framework, the university has the ability to examine variants in a million DNA locations to discover ‘the mechanisms of cancer and how networks of genes drive cancer susceptibility and outcome’.
Data-driven university research is a driving force behind the search for a cancer cure. With their large computing power, further universities have stepped up to support innovative research.
Read more about how other universities are putting their efforts into finding a cure for cancer using big data, here.
Are you sharing more data with Google than you have to?
There is a new method to limit how much of your data you need to share and is being offered to companies for free.
As a business, it is important to protect all aspects of your company including privacy, security, competitive advantage, intellectual property. Very little data needs to be shared with employees, contractors and third parties.
This may seem like an obvious statement, but it is surprising how much data is unnecessarily shared with cloud providers.
The time and effort required to take away data that the third party doesn’t actually need the data that is necessary can make the ROI seem unattractive. This is especially true when executives play down the risk of anything bad happening.
Another reason why unnecessary data is being shared is to do with technological restrictions. When big enterprises handle data – particularly data that is either generated by or managed by mobile devices – it makes it really problematic to simply separate the critical from the non-essential.
Researchers at the Swiss Federal Institute of Technology in Lausanne may have found the answer to deal with these issues. Their approach restricts what data is shared and uses an encryption method that permits data to be crunched while still encrypted.
Applied AI is here
Despite the access and availability of electronic medical records, financial data, clinical data, and advanced techniques promising to revolutionise the healthcare industry – it hasn’t really happened.
The healthcare industry was not really prepared for the enormity and complexity of the data challenge, and that, over time, with the next EMR (electronic medical record) implementation, that healthcare will be situated to gain the benefits.
The more data we have at our disposal, the more likely questions there are and the lower the possibility that we will ask the one that creates new value for the patient, the provider or the payer.
There may be suggestions that predictive analytics solves the problem, but it too is hypothesis motivated – just in a different way. With predictive analytics, the set of chosen variables, the choice of algorithms is, in effect, estimates as to what will create the best result.
Big data and wearable tech
Whilst patients will physically and mentally be more aware of their health condition, they should be aware that their health information is subject to exposure via hospital system hacking targeting electronic health records (EHRs).
With greater access to information means the need for tighter security protocols in order to safeguard sensitive information on patients. However, there is also the prospect for more jobs to open up in app development, cyber security, information systems, and predictive analytics.
With this in mind, there are several ways in which the application of big data can benefit public health.
Smart watches may seem advanced as they detect and monitor your heart rate but what about wearing a skin patch to perform blood tests remotely, or an earbud to detect abnormal heartbeats? These are just a few of the innovative technology products that are in the process of being developed.
Smart cities are using predictive analytics to improve issues related to public health – for example, food safety and lead contamination. Chicago’s Department of Public Health’s (CDPH) recent partnership with the Department of Innovation and Technology put big data into action to analyse food-related data.
In the midst of the shortage of doctors and nurses, international public health organisations have been required to make hard decisions about which groups are in the most urgent need of treatment. The Ebola crisis is the most recent event that inspired the use of various platforms, apps, and services to gather data and communication and provide real-time information about the most recent outbreak situations and developments.
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