18,515 research outputs found
Living IoT: A Flying Wireless Platform on Live Insects
Sensor networks with devices capable of moving could enable applications
ranging from precision irrigation to environmental sensing. Using mechanical
drones to move sensors, however, severely limits operation time since flight
time is limited by the energy density of current battery technology. We explore
an alternative, biology-based solution: integrate sensing, computing and
communication functionalities onto live flying insects to create a mobile IoT
platform.
Such an approach takes advantage of these tiny, highly efficient biological
insects which are ubiquitous in many outdoor ecosystems, to essentially provide
mobility for free. Doing so however requires addressing key technical
challenges of power, size, weight and self-localization in order for the
insects to perform location-dependent sensing operations as they carry our IoT
payload through the environment. We develop and deploy our platform on
bumblebees which includes backscatter communication, low-power
self-localization hardware, sensors, and a power source. We show that our
platform is capable of sensing, backscattering data at 1 kbps when the insects
are back at the hive, and localizing itself up to distances of 80 m from the
access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang,
In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201
Rosetta Brains: A Strategy for Molecularly-Annotated Connectomics
We propose a neural connectomics strategy called Fluorescent In-Situ
Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC),
leveraging fluorescent in situ nucleic acid sequencing in fixed tissue
(FISSEQ). FISSEQ-BOINC exhibits different properties from BOINC, which relies
on bulk nucleic acid sequencing. FISSEQ-BOINC could become a scalable approach
for mapping whole-mammalian-brain connectomes with rich molecular annotations
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