Building wireless sensor networks with biological cultures: components and integration challenges

• Published in: International journal of parallel, emergent and distributed systems Vol. 32; no. 1; pp. 56 - 73
• Main Authors: Christophe, Francois, Laukkarinen, Teemu, Mikkonen, Tommi, Massera, Jonathan, Andalibi, Vafa
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.01.2017; Taylor & Francis Ltd
• Subjects: Bio-integration in ubiquitous systems; biological neural networks; Communication; Computation; Computer networks; CUDA; high-performance computing; Mathematical models; Neural networks; Optics; Remote sensors; Robots; spiking neural networks; Wireless networks
• ISSN: 1744-5760; 1744-5779
• DOI: 10.1080/17445760.2016.1145220

The development of wireless sensor networks (WSNs) struggles with limited computing, communication, and energy resources. Bio-Integrated Systems (BISs) contain cultured cells that perform certain tasks. For instance, neurons can work as brains for robots. BISs could provide solutions to overcome WSNs resource constraints. Biological entities integrating in computing hardware gains interest especially in robotics. This interest is due to the potentials of such integration in deep learning capacity, massive parallelism, energy savings, and communication and integration with living subjects. This paper collects existing BISs research and provides research motivations for Bio-Integrated WSNs (BI-WSNs). BI-WSNs solutions for improving energy preserving, sensing, processing, and communication are proposed and supported with existing examples. Further, on-going research on integrating neural networks in WSNs is presented. Challenges related to protection of biological entities from external environment are discussed. Finally, a prospective model of BI-WSNs consisting in optogenetic communication combined with neural network processing is given. This graphical abstract represents the different components of a node of a sensor networks. This paper studies the possibilities to replace each of these components with a biological counterpart enabling similar functionalities. The benefits and challenges for the development of such biological sensors, named Bio-Integrated Wireless Sensor Network (BI-WSN), are discussed in this study.