Professor Mario Köppen
Editor in Chief, Applied Soft Computing (ASOC)
Editor in Chief, International Journal of Soft Computing and Networking (IJSCN)
Associate Editor, The International Journal of Hybrid Intelligent Systems (IJHIS)
Department of Computer Science and Electronics
Graduate School of Creative Informatics
Kyushu Institute of Technology. Japan
Smart Farming: The documentation challenge
These days, complex food supply chains, characterized by the production, distribution, transport, processing, retail and consumption of food get more and more entitled to various risks: contamination, domino effects caused by the inherent push&pull two-sided causality, contamination propagation (incl. virus spread), resource depletion, origination and quality disputes. Here, farming is not only farm production of food at some location, but has to be seen by its effects on the whole chain. This is a challenge for any novel concept of smart farming. We discuss the various stages and the related technology challenges.
The novel viewpoint here is to take on the documentation of the whole system. The documentation aspects in more detail refer to: new sensors data logs, incl. polarization, thermal, multi-spectral imaging and wearables integration, incl. hierarchical classification and prediction tasks; security, esp. the tracking of ingredients mixtures, or the special multi-factor and small scale modality of blockchain technology. Further on, we need to explore new computational intelligence solutions for the task of retrieval of data to give it into the hand of consumers, a broad avenue for fuzzy information processing. Novel optimization approaches are needed for the interplay of the various optimization modalities of the food system: farmers’ “look after things” as a correction-driven cognitive ability of humans, scheduling with respect to distribution and transport stage, efficiency and non-physical optimization for the processing and manufacturing stage, and the price-driven retail and consumption stage. All those tasks have been studied in perfect isolation so far, but to keep them in a global balance poses new requirements on optimization algorithms. We might take inspiration from the microbiome and how it achieves it’s task to keep an organism up and running. As a last step, how about moving the food system from a chain to a circle and base it on circular economy, to tackle the problem of incentives driving the system and avoid future harm caused by the classical domino effect?
The whole story has just opened its first chapter. But we have already promising technology at hand, incl. Big Data and IoT, global communication, low cost sensors, and Computational Intelligence. Those can surely support to move away from the isolated efficiency race per food system stage to the safety-oriented, open, holistic and versatile documentation point of view towards the design and conception of a future smart farming system.
Kevin K.W. Ho, Ph.D.
Professor of Management Information Systems, School of Business & Public Administration, University of Guam
Co-Editor, Library Hi Tech (SSCI-Indexed Journal: 2018 Impact Factor: 1.256)
Chair, SCUBP of Faculty Senate (AY 2018-2020)
Business Division Assessment Chair (AY 2019-2020)
Dissemination of online (fake) health information: Habits, catalyst, and barriers
While the Internet can be a convenient medium for seeking health information, it is also easy for anyone to publish online health information without any professional gatekeeping. As a result, such information that circulates online may not necessarily be correct. The online health misinformation may lead to many sequences, such as unnecessary stress, delay of screening, and misbelief on ineffective treatment options. The consequence of online health misinformation in this aspect has drawn the attention of researchers from different fields, including information systems, healthcare, and communication. In this presentation, we will review how online news consumption habits are related to the ability to identify online health misinformation; and how the users’ perception of believability, financial incentives, and legislation that regulated online misinformation would affect the likelihood of sharing health information.