A Machine Learning Driven IOT Wireless Sensor Network for Digital Logistics in Remote and Fragile Environments

During the previous Phases of this project, the Ryalinks team developed and tested the core technology that delivers the functionality of this platform: modular extremely low-power sensor hardware modules capable of operating on 2 AA batteries for years, a hierarchical robust wireless mesh network with self-healing capabilities, and a back-end software to receive, report and broadcast sensor data in real-time. In addition, a single use-case for Engine Cans was implemented and tested.   Based on feedback received from discussions with various SYSCOMMS across the Navy, it would be very useful for the leadership and decision makers across these SYSCOMMS to see additional use cases for this technology. As such, the primary focus of this expansion effort is to demonstrate the applicability of the Ryalinks technology towards enabling additional use-cases that can alleviate cost and improve operational efficiency and readiness in potentially multiple SYSCOMMS across the Navy. In the following sections, a few of these additional use cases are outlined. It is important to note that these new use cases were communicated to the Ryalinks team by the ground support team at various locations across North Island. It is expected that as we continue to engage with NAVSUP and NAVAIR leadership throughout this expansion effort, the scope and definition of these use cases will be further fine-tuned to adapt to the specific use-case scenarios as outlined by the customer leadership and decision makers.  Throughout engagements, demonstrations and discussions, the Ryalinks team will attempt to quantify the benefits of adoption of this technology and build the Return on Investment case for why each SYSCOMM should adopt this technology. This ROI analysis needs to happen when an initial implementation of these use cases has been built, tested and demonstrated (the main focus of this expansion effort). Upon successful demonstration of these use cases, the cost of this solution and the operational impacts can be quantified, thus enabling a meaningful ROI analysis.   Additionally, every additional test will improve the technical maturity of the product. The Ryalinks engineering team will attempt to stress the network at every site which will have slightly different RF characteristics. These tests will be key towards enabling a successful HERO test when necessary. At every demo, it is expected that invaluable feedback will be received towards the usability of the back-end system. This will eventually lead to the integration of the Ryalinks back-end into the required proprietary Navy back-ends such as NADACS. Whether or not the actual integration with these back-end networks are completed as part of this expansion effort will depend on the requirements of the SYSCOMM that will be interested in ultimately adopting this technology.