THE BIOLOGICAL INTERNET
Athanasios V. Vasilakos, Lulea University of Technology, Sweden
ABSTRACT: The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, targeted drug delivery, interfacing artificial devices with neural systems and it can serve as countermeasure for surveillance (security) against nuclear, biological and chemical attacks. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system (Internet of Bio-Nano Things).
SHORT BIO: Athanasios V. Vasilakos is currently Full Professor at Lulea University of Technology (Sweden) in the Department of Computer Science. He has authored or co-authored over 250 technical papers in major international journals and conferences. He is author/coauthor of five books and 20 book chapters. His main research topics include: Networks, Sensor nets/IoTs, Cloud Computing, Green Networking, Algorithms, Security & Privacy, Big Data, Body Area Network (BANs), Medical Informatics, Molecular Nano-Networks. He is an ISI Highly cited researcher, with 13600 citations, h-index= 70 and with 36 works with more than 100 citations each. Prof. Vasilakos has served as General Chair, Technical Program Committee Chair for many international conferences and he is serving/ has served as an Editor for many leading journals, such as IEEE Transactions on Information Technology in Biomedicine (2009-2012), IEEE Transactions on Network and Services Management (2011-2014), IEEE Transactions on Cloud Computing (Today), IEEE Transactions on Information Forensics and Security (Today), IEEE Transactions on Cybernetics (Today) and IEEE Transactions on Nanobioscience (Today).
SUSTAINABLE SMART WEARABLES: TOWARD SENSOR ANALYTICS WITH HARVESTED ENERGY
Luca Benini, University of Bologna, Italy
ABSTRACT: Wearables devices are becoming ubiquitous in our lives, replacing classically passive artifacts like bracelets, shoes, clothes. These sensor-rich connected devices are going to produce a mind-boggling quantity of data and potentially useful information. However, data alone do not provide value unless we can turn them into actionable, contextualized information. Sensor Data Analytics (SDA) allows us to gain new insights through batch-processing off-line analysis of raw sensor data, but in order to make it scalable and effective for the user, we should make a big part of the SDA pipeline real-time and near-sensor. Current wearable devices perform only very limited filtering, feature extraction and classification on-board and usually leverage smart-phones for computationally intensive tasks. Even with this limited local intelligence approach, current wearables are battery-limited and need frequent recharges.
In this talk I will present our experience in building smart wearable devices that processes the data fully, in situ, with a power draw compatible with wrist-wearable energy harvesters. This approach significantly reduces the amount of data to be transmitted and the required human intervention, including battery recharging. I will describe the main technological building blocks, our system integration efforts, the application challenges emerging from our field trials and provide insights on future research directions.
He received a Ph.D. degree in electrical engineering from Stanford University in 1997. Dr. Benini's research interests are in energy-efficient system design and Multi-Core SoC design. He is also active in the area of energy-efficient smart sensors and sensor networks for biomedical and ambient intelligence applications.
He has published more than 700 papers in peer-reviewed international journals and conferences, 4 books and several book chapters. He is a Fellow of the IEEE and a member of the Academia Europaea.