The EU MSCA, Region Bretagne, and IMT-Atlantique co-funded the POWER-PA project. The project aims to study and develop energy- and spectrum-efficient wireless communication network protocols using model and machine learning-based techniques for precision/smart farming/agriculture. IMT-Atlantique MEE Department hosts the research with collaborators from INPT (Morroco), WUR (Netherlands), and CSIR-INSTI (Ghana).  This page serves as the central point for information, links, and updates on the research progress and deliverables, which are openly accessible. 

The Project is funded by 

• MSCA-CoFund, BIENVENUE

• IMT Atlantique Research Fund

Project Scope:  The future of Internet-of-Things (IoT) will consist of billions of interconnected devices and network interactions. These IoT networks will extend to agriculture for accurate and real-time monitoring and running of agriculture under the paradigm of Precision Agriculture (PA). With advancements in wireless communication technologies for IoT networks, there are still issues of high interference, high latency, inefficient spectrum usage, and low reliabilities, which need to be mitigated. These issues also affect IoT network technology applications in PA. It is, therefore, imperative to mitigate these issues with better efficient design, optimization, and evaluation of IoT networks in PA to improve real-time farm operation. Motivated by these concerns, the Power-PA project aims to provide algorithms/protocols and medium access designs for efficient and effective resource and spectrum allocation, interference management, lower latency, and higher reliability to achieve a high-performance PA IoT network. 

Publications and open-access (data and codes) links:

Journals:

[3] Derek Kwaku Pobi Asiedu, Sumaila Anning Mahama, Mustapha Benjillali, Ji-Hoon Yun, and Samir Saoudi, "Energy-Efficiency with Massive MIMO MU-NOMA in Symbiotic BackCom IoT Networks", in IEEE Communication Letters, vol. 28, no. 10, pp. 2318 - 2322, Oct. 2024. 

[2] Samuel Kwamena Menanor, Derek Kwaku Pobi Asiedu, Mustapha Benjillali, Samir Saoudi, and Kyoung-Jae Lee, "Energy-Efficient IRS-Assisted MU-mMIMO and WP-BackCom  Symbiotic Radio IoT Network", submitted to IEEE Internet-of-Things Journal, Aug. 2024

[1]  Derek Kwaku Pobi Asiedu, Kwabena Ebo Bennin, Dennis Gookyi, Mustapha Benjillali, and Samir Saoudi, "Precision Agriculture Deep Neural Network Driven Multi-Path Multi-Hop Plant Image Noisy Data Transmission and Plant Disease Detection", Submitted to Annals of Telecommunication, Springer, Jun. 2024.

Conferences:

[4] Derek Kwaku Pobi Asiedu, Kwabena Ebo Bennin, Mustapha Benjillali, and Samir Saoudi, "Energy-efficient device-to-device routing in a three-Tier Symbiotic Radio IoT Network", accepted for presentation Proc. IEEE Wireless Communication and Networking Conference (WCNC), Milan, Italy, March 2025.

[3] Derek Kwaku Pobi Asiedu, Kofi Ofori-Amanfo, Mustapha Benjillali, Ji-Hoon Yun, and Samir Saoudi, "Sum-rate Maximization of Symbiotic Multi-V2X MISO and Multi-RIS BackCom with Imperfections", in Proc. IEEE Vehicular Technology Conference (VTC) Fall, Washington DC, USA, Oct. 2024. 

[2] Derek Kwaku Pobi Asiedu, Kwadwo Ofori-Amanfo, Kwabena Ebo Bennin, Mustapha Benjillali, Kyoung-Jae Lee and Samir Saoudi, "Precision Agriculture Deep Neural Network Driven Multi-Hop Plant Image Noisy Data Transmission and Plant Disease Detection", in Proc. IEEE International Conference on Signal, Image, Video and Communications (ISIVC), Marrakesh, Morocco, May 2024. [In-Person Presentation]

[1] Richard Boateng Nti, Derek Kwaku Pobi Asiedu, Mustapha Benjillali, Ji-Hoon Yun, and Samir Saoudi, "Multi-Source Cognitive BackCom with Temporal Combining for Reliable IoT Communication", in Proc. IEEE Communication Theory Workshop (CTW), Banff, Canada, 2024. [Poster Presentation]