Trends Identified
Big Data-based Infectious Disease Prediction and Alert System
(Definition) Technology that predicts the potential regional spread of infectious diseases, by utilizing diverse data such as the dissemination process of diseases, infected patients, and population data. (Application) Real-time big data analysis assists the government authority with disease management policy and improves the infectious disease control and management plan at the national level, securing public health and safety.
2016
KISTEP 10 Emerging Technologies 2016
South Korea, Korea Institute of S&T Evaluation and Planning (KISTEP)
Big data, the Internet of Things and artificial intelligence
Big data and IoT are new digital developments that make it possible to optimize business operations and facilitate the creation of new products, services and industries. The possibility of collecting unlimited amounts of data through Internet-connected sensors and monitoring of the web and social media allows prediction of demand, estimation of rural incomes (based on mobile phone activity) and anticipation of civil unrest. While such technologies add to the existing toolkit for development, the availability of fine-grained and increasingly personal data also introduces new risks (see section D.2). Such technologies therefore merit attention from policymakers. In the last few years, artificial intelligence has become a major focus of attention for technologists, investors, governments and futurists. Since it was first proposed more than 60 years ago, artificial intelligence has experienced periods of progress but also of stagnation, when it has been virtually sidetracked while other technologies advanced exponentially. However, recent breakthroughs have led to major advances, driven by machine learning and deep learning, facilitated by access to huge amounts of big data, cheap and massive cloud computing, and advanced microprocessors (Kelly, 2016:38–40).Artificial intelligence now includes image recognition that exceeds human capabilities and greatly improves language translation, including voice translation through natural language processing, and has proved more accurate than doctors at diagnosing some cancers.
2018
Technology and Innovation Report 2018
UNCTAD
Bigdata Analytics for Healthcare
(Definition) The technology collects patients’ hospital service use, medication, treatment and other various data including medical records to analyze useful information. (Application) Based on the result, the technology can provide prevention of diseases and personal healthcare which in turn reduces the medical cost.
2015
KISTEP 10 Emerging Technologies 2015
South Korea, Korea Institute of S&T Evaluation and Planning (KISTEP)
Bigdata based crime prediction
(Definition) Analyze past crime data and comprehend the pattern to predict the place and time when crimes are likely to occur. (Application) Provide detailed analysis of the site and the type of crimes that occur near the address in order to prevent the crime as well as deploy more police force. (Impact) It will be an effective strategy to reduce the crime rate, however, will cause over-spilling of personal data. If big data is used for public parts, EU reports that there will be € 150~ 300 billion economic advantage occurring.
2014
KISTEP 10 Emerging Technologies 2014
South Korea, Korea Institute of S&T Evaluation and Planning (KISTEP)
Bio Computing – Using Nature‘s Computation
One way to solve the limits of current miniaturization is to use biological molecules for computing. Biological computing uses synthesized biological components – mostly DNA – to store and manipulate data, analogous to processes in the human body. It computes by using enzymes that react with DNA strands. Biological computing allows very small and fast and potentially paralell computing process, with great accuracy and unmatched energy efficiency. The first DNA based computer was launched in 2002 but the technology is still in very early prototype stage, with the MIT being one of the most prolific research institutes. Present barriers result in low accuracy, the need for new methodologies, and interoperability issues with other computing systems. Use cases would be ID cards, DNA chips, cryptography, and genetic programming.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Bio Stamp
(Definition) The technology is a sensor which can be attached to skin in order to monitor the person’s health. (Application) The technology allows the elderly to simply monitor their health as when the device is attached to the skin it can automatically monitor live the blood pressure, temperature, brain activities and so on, then send the data.
2015
KISTEP 10 Emerging Technologies 2015
South Korea, Korea Institute of S&T Evaluation and Planning (KISTEP)
Bio-electric interfaces
Bioelectronic interfaces make it possible to integrate electronic devices with biological tissues (often membranes of nerve cells) to carry out vital processes and bodily functions under various conditions and environments. From a medical viewpoint this is necessary to achieve connections between implantable chips, bionic prosthetic limbs, implanted artificial sensory organs, and the electrodes of various biotechnical systems and medical devices. Electronic sensory organs are likely to be developed, as well as prosthetics made from new materials with increased compatibility.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Bio-plastics
Primarily driven by non-climate related environmental concerns, notably plastic trash in the ocean, biodegradable plastic is likely to make inroads as the technology develops, with potentially upward of 50% of plastics replaced by non- oil based alternatives by 2040, 8 including potentially with nanotechnology solutions.
2018
The bigger picture- The impact of automation, AI, shared economy on oil demand
The 2° Investing Initiative
Bio-plastics
Example of Organizationsactive in the area: NatureWorks (US), Gruppo MAIP (Italy), Genomatica (US), Green Dot Bioplastics (US).
2018
Table of disruptive technologies
Imperial College London