People's health records in the world: the most urgently needed resources in the medical field, brain atlas: understanding how all parts of the body work, coordinating the supply of uranium raw materials around the world, tracking weaponization activities and energy supply, and other world issues that people are most concerned about, giant enterprises such as IBM and Google have begun to overcome such difficult challenges, which is very exciting.
Despite the continuous improvement of computing performance, storage capacity and analysis technology, some practical challenges are still too great for big data to cope with. In today's article, we will explore five such problems-see how to solve them.
What if big data can further solve the world's problems outside the traditional field? So far, giant companies such as IBM, Google and Hewlett-Packard have begun to deal with this difficult challenge, including analyzing how many vehicles will pass the bridge on the busy highway or calculating how many users will view a small advertisement in the web browser. Google even announced an ambitious plan, saying it would solve the historic problem of human aging.
But there are still several world-wide problems waiting for us to overcome. In some cases, the data needed for analysis is completely untraceable. In other cases, computers that can handle such a huge amount of data have not been invented. At present, there are five topics worthy of our attention. Will big data technology companies stand up and solve problems? We wait for time to bring the answer.
World People's Health Records: the most urgently needed resource in the medical field
Most people have an electronic health record (HER), but its content is quite limited-even it only contains the basic results of the latest health examination. At present, tools and technologies that can support the world health record database have been put in place. Once such a global database appears, pharmaceutical companies can analyze it to develop vaccines and drugs that people need most-that is, make priority choices according to the actual needs of the supply chain.
Since the prospect is bright, why haven't we benefited from it? This is because there is still a lack of feasible mechanisms to access global data. MikeMiller, co-founder and chief scientist of Cloudant, a distributed database provider, said: "Health records are kept in many isolated systems, and data holders do not have enough motivation to share this information. "Even if we really put all the data together, we still need to fully optimize it through machine learning algorithms and real-time analysis. This is exactly what we are currently working on. "
Atlas of the human brain: understanding how all parts of the body work.
The human brain model can bring great help to scientific research. Doctors can observe the growth of tumors or understand how the brain controls other organs of the body through a series of functions. At present, many scientific projects, including the European Brain Project, are trying to create a brain simulation system in the next decade.
What are the obstacles? To complete this work, we need a supercomputer with a computing speed thousands of times higher than the current level. There are millions of neurotransmitters in the brain, which are interrelated, and they are the same as the "data" we are exposed to.
"Computing on this scale requires us to leave the traditional silicon chip field and move towards the biochip era-this is a prerequisite for molecular computing," Olberg explained. McGee, former Deputy Assistant Secretary of State in Clinton Administration (in charge of transportation system technology policy), is now a professor at Howard University. "From an intuitive point of view, molecular computing is 750 times faster than traditional silicon chips in data management. Only such a mechanism can deal with the cognitive mystery of relationships in the brain system. "
Coordinating the supply of uranium raw materials around the world: tracking weaponization activities and energy supply
There is no doubt that collecting any data on a global scale will be an extremely difficult task, but tracking the global supply of uranium raw materials has at least positive significance-of course, provided that all pieces of information can be seamlessly spliced together.
CEOKeithCooper of Connotate Company, a data collection company, pointed out that we can only solve some of these problems at present, because some countries have not disclosed their records of uranium raw material supply. "At present, although many countries with rich uranium reserves already have convenient internet systems, they still refuse to announce their resource flows in a standardized way." Fortunately, it is not too difficult to calculate the macro situation-after all, the number of countries that have put uranium raw materials into weaponization is limited.
What we really need to track and master is the most precious enriched uranium in the world, accounting for only 15%, he explained. "We need to identify and track all sales activities (through black market or legal channels) and mineral distribution related to enriched uranium, and make statistics through forums, blogs, regulatory agencies and other peripheral systems, including reports from governments and non-governmental organizations on the production data and mining activities of uranium raw materials. In order to process the collected results, we also need to design an intelligent man-machine communication scheme. "
Global real-time crime data: more proactive policing capabilities
Many local law enforcement departments already have a wealth of crime data, and the police can easily access the database of criminal records in their own police cars, so as to respond according to the specific situation of criminal suspects.
What are the obstacles? Miller of Cloudant said that these data only contain past crimes and cannot reflect criminal activities that have just happened or are in progress. In the process of being unable to stop criminal activities, the police can only be forced to take more passive measures.
But Miller pointed out that the situation has changed. For example, the police in Oakland, California have been equipped with acoustic monitors to identify gunshots. Technicians call it "ShotSpotter", which can use big data analysis mechanism to track potential crime sites, and police officers immediately go to the corresponding locations according to the analysis conclusions. The advantages brought by real-time crime data are not limited to the field of law enforcement: TruliaLocal hotspot map can provide criminal activity reports, thus helping house buyers to choose a friendlier and safer living environment.
Tracking the whereabouts of children: a better and more timely amber.
Today, we have many methods to report missing children, such as AmberAlert system adopted by the United States. However, the biggest problem with these notification mechanisms is that they can only initiate reminders afterwards. The necessary technology for tracking children's location already exists. At present, most smartphones can send their current location to their parents through Google's location report function. At the same time, Volkswagen's Car-Net and Ford's MyKey application can also send reports when teenagers drive to special geographical locations.
What are the obstacles? Analysis. JaisonManian, vice president of digital marketing company RoundarchIsobar, pointed out that forecasting technology can help us. Big data vendors can analyze children's behavior patterns, provided parents are willing to share relevant data.
"Predictive analysis can track children's daily action patterns and immediately warn parents when there are serious deviations," he said. As long as the early warning conditions are met, the information will be sent in real time-this can effectively prevent the occurrence of major accidents.
The above is what Bian Xiao shared with you about the five world-wide problems that big data urgently needs to overcome. For more information, you can pay attention to the global ivy and share more dry goods.