Abstract
This chapter presents several perspectives of the smart dust mesh based on theInternet of Everything, Everywhere (IoEE). Smart dust surveillance finds application in military and security area (monitoring of people and products), in enhancing ambient interaction (for people with visual, motor, and auditory impairments), e-health monitoring, environmental surveillance of temperature, light intensity, sound, pressure, particle suspensions (PM 0.1–10) in the air, humidity, harmful chemicals, vibrations, magnetic, and electrical fields. The goal is to survey climatic changes, seismic activities, air emissions, and water pollution in case of mines or extremely industrialized cities. However, it is of interest to note its applicability in smart city IoT; the smart dust surveillance also comes with disadvantages, such as privacy, control, maintenance, and high costs. The device comprises clusters of smart interconnected small parts (MEMS, memristors in micro/nano size), which add to the cost. The smart dust networked mesh should be lightweight and maintained by passive power generators which rely on harvesting light, vibration, heat. According to DARPA reports (ElectRx program 2016), the smart dust such as neural dust “motes” that are implantable monitors nerve activity by recording wirelessly. In the field of health surveillance, ElectRx program that is developed by neural smart dust is capable of treating pain, general inflammation, post-traumatic stress, severe anxiety, and trauma by precise noninvasive monitoring of the patient’s peripheral nervous system. The prototype for neural dust is millimeter size small, with the possibility of manufacturing individual motes of 1 cubic millimeter or even as small as 100 microns per side.
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Acknowledgments
This work has been supported in part by UEFISCDI Romania and MCI through projects CitiSim, ESTABLISH, PARFAIT and WINS@HI, funded in part by European Union’s Horizon 2020 research and innovation program under grant agreement No. 826452 (Arrowhead Tools), No. 787002 (SAFECARE), No. 777996 (SealedGRID) and No. 813278 (A-WEAR).
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Aileni, R.M., Suciu, G., Serrano, M., Maheswar, R., Valderrama Sakuyama, C.A., Pasca, S. (2020). The Perspective of Smart Dust Mesh Based on IoEE for Safety and Security in the Smart Cities. In: Rani, S., Maheswar, R., Kanagachidambaresan, G., Jayarajan, P. (eds) Integration of WSN and IoT for Smart Cities. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-38516-3_9
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