J
Juha-Pekka Soininen
Researcher at VTT Technical Research Centre of Finland
Publications - 81
Citations - 2661
Juha-Pekka Soininen is an academic researcher from VTT Technical Research Centre of Finland. The author has contributed to research in topics: Control reconfiguration & SystemC. The author has an hindex of 18, co-authored 75 publications receiving 2243 citations.
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Proceedings ArticleDOI
A network on chip architecture and design methodology
Shashi Kumar,Axel Jantsch,Juha-Pekka Soininen,Martti Forsell,Mikael Millberg,Johnny Öberg,Kari Tiensyrjä,Ahmed Hemani +7 more
TL;DR: A packet switched platform for single chip systems which scales well to an arbitrary number of processor like resources which is the onchip communication infrastructure comprising the physical layer, the data link layer and the network layer of the OSI protocol stack.
Journal ArticleDOI
Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture
Carlos Kamienski,Juha-Pekka Soininen,Markus Taumberger,Ramide Dantas,Attilio Toscano,Tullio Salmon Cinotti,Rodrigo Filev Maia,André Torre Neto +7 more
TL;DR: Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.
Journal ArticleDOI
Semantic Interoperability Architecture for Pervasive Computing and Internet of Things
Jussi Kiljander,Alfredo D'Elia,Francesco Morandi,Pasi Hyttinen,Janne Takalo-Mattila,Arto Ylisaukko-oja,Juha-Pekka Soininen,Tullio Salmon Cinotti +7 more
TL;DR: This work presents a novel semantic level interoperability architecture for pervasive computing and IoTs that conforms to the common IoT-A architecture reference model (ARM), and maps the central components of the architecture to the IoT-ARM.
Proceedings ArticleDOI
Empowering healthcare IoT systems with hierarchical edge-based deep learning
Iman Azimi,Janne Takalo-Mattila,Arman Anzanpour,Amir M. Rahmani,Juha-Pekka Soininen,Pasi Liljeberg +5 more
TL;DR: This paper investigates the feasibility of deploying the Convolutional Neural Network (CNN) based classification model as an example of deep learning methods in a hierarchical computing architecture, and demonstrates a real-time health monitoring for a case study on ECG classifications.
Proceedings ArticleDOI
A digital twin for smart farming
Rafael Gomes Alves,Gilberto Souza,Rodrigo Filev Maia,Anh Tran,Carlos Kamienski,Juha-Pekka Soininen,Plinio Thomaz Aquino,Fabio Lima +7 more
TL;DR: It is concluded that the system can gather data from the soil probe and display its information in a dashboard which enables for further deployment of more soil probes and other monitoring and controlling devices to create a fully operating digital twin.