logo EDITE Keoma BRUN-LAGUNA
Identité
Keoma BRUN-LAGUNA
État académique
Thèse en cours...
Sujet: Deterministic Networking for the Industrial Internet of Things
Direction de thèse:
Encadrement de thèse:
Laboratoire:
Voisinage
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
oai:hal.archives-ouvertes.fr:hal-01312685
PEACH: Predicting Frost Events in Peach Orchards Using IoT Technology
International audience
EAI Endorsed Transactions on the Internet of Things https://hal.inria.fr/hal-01312685 EAI Endorsed Transactions on the Internet of Things, 2016ARRAY(0x7f04012aa1a8) 2016-06-01
oai:hal.archives-ouvertes.fr:hal-01311527
A Demo of the PEACH IoT-based Frost Event Prediction System for Precision Agriculture
International audience
IEEE International Conference on Sensing, Communication and Networking (SECON) https://hal.inria.fr/hal-01311527 IEEE International Conference on Sensing, Communication and Networking (SECON), Jun 2016, London, United Kingdom. 2016ARRAY(0x7f040051fed8) 2016-06-27
oai:hal.archives-ouvertes.fr:hal-01327798
SOL: An End-to-end Solution for Real-World Remote Monitoring Systems
International audience
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) https://hal.inria.fr/hal-01327798 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Sep 2016, Valencia, Spain. 2016ARRAY(0x7f04014de1f8) 2016-09-04
oai:hal.archives-ouvertes.fr:hal-01361333
(Not so) Intuitive Results from a Smart Agriculture Low-Power Wireless Mesh Deployment
International audience
A 21-node low-power wireless mesh network is deployed in a peach orchard. The network serves as a frost event prediction system. On top of sensor values, devices also report network statistics. In 3 months of operations, the network has produced over 4 million temperature values, and over 350,000 network statistics. This paper presents an in-depth analysis of the statistics, in order to precisely understand the performance of the network. Nodes in the network exhibit an expected lifetime between 4 and 16 years, with an end-to-end reliability of 100%. We show how – contrary to popular belief – wireless links are symmetric. Thanks to the use of Time Slotted Channel Hopping (TSCH), the network topology is very stable, with ≤5 link changes per day in the entire network.
CHANTS'16 https://hal.inria.fr/hal-01361333 CHANTS'16, Sep 2016, New York City, United States. 2016, <http://www.acm-chants.org/>. <10.1145/2979683.2979696> http://www.acm-chants.org/ARRAY(0x7f040001eb98) 2016-09-07
oai:hal.archives-ouvertes.fr:hal-01364041
Demo: SierraNet: Monitoring the Snowpack in the Sierra Nevada
International audience
Next-generation hydrologic science and monitoring requires real-time, spatially distributed measurements of key variables including: soil moisture , air/soil temperature, snow depth, and air relative humidity. The SierraNet project provides these measurements by deploying low-power mesh networks across the California Sierra Nevada. This demo presents a replica of the end-to-end SierraNet monitoring system deployed in the Southern Sierra. This system is a highly reliable, low-power turn-key solution for environmental monitoring.
CHANTS'16 https://hal.inria.fr/hal-01364041 CHANTS'16, Oct 2016, New York City, United States. 2016, <http://www.acm-chants.org/>. <10.1145/2979683.2979698> http://www.acm-chants.org/ARRAY(0x7f03ffff6f60) 2016-10-07