The expansion of the Internet of Things (IoT) in the battlefield, Internet of Battlefield Things (IoBT), gives rise to new opportunities for enhancing situational awareness. To increase the potential of IoBT for situational awareness in critical decision making, the data from these devices must be processed into consumer-ready information objects and made available to consumers on demand. To address this challenge we propose a workflow that makes use of natural language processing (NLP) to query a database and return a response in natural language. Our solution utilizes Large Language Models (LLMs) sized for edge devices to perform NLP, as well as a graph database. These types of databases are well suited for the dynamic, connected networks pervasive in the IoBT. Our architecture employs LLMs for both mapping questions in natural language to Cypher database queries as well as to summarize the database output back to the user in natural language. We evaluated several medium-sized LLMs for both of these tasks on a database representing publicly available data from the US Army's Multi-purpose Sensing Area Multi-Purpose Sensing Area (MSA) at the Jornada Range in Las Cruces, NM. We observe that Llama 3.1 (8 billion parameters) outperforms the other models across all considered metrics. Most importantly, we note that, unlike current methods, our two step approach allows the relaxation of the Exact Match (EM) requirement of the produced Cypher queries with ground truth code and, in this way, it achieves a 19.4% increase in accuracy. Our workflow lays the groundwork for deploying LLMs on edge devices to enable natural language interactions with databases containing information objects for critical decision making.
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Title
Natural Language Interaction with Databases on Edge Devices in the Internet of Battlefield Things
Publication Details
MILCOM IEEE Military Communications Conference, pp.838-843
Resource Type
Conference proceeding
Conference
IEEE Military Communications Conference (MILCOM): MILCOM 2025 (Los Angeles, California, USA, 10/06/2025–10/10/2025)