RIMNI SPECIAL ISSUE - Future of AI in Multi-Sensor Imaging and Fusion

Deadline Date: 31 July 2026

1) The issue introduction includes the background and the importance of this research area.

The future of AI is the approach to integrate numerous complementary sensors to overcome the constraints of individual sensors operating separately. Finding a balance between edge computing capabilities and sensor fusion is a critical area of development. Artificial intelligence has the potential to increase workplace productivity, which will benefit people by allowing them to accomplish more work. AI will eventually replace laborious or hazardous jobs, freeing up the human workforce to concentrate on jobs for which they are better suited, including those requiring empathy and creativity. In the realm of artificial intelligence, sensor fusion pertains to the procedure of combining information from various sensors to generate well-informed judgments or deductions. This is a compact, handheld device that is compatible with tablets and smartphones.

Using AI algorithms, AI ultrasonography assists healthcare professionals in low-resource settings in monitoring pregnancies and identifying high-risk pregnancies. These gadgets don't require additional radiology or obstetric training for nurses and midwives to utilize. Research on crops, illnesses, pests, weeds, soil quality, and climate will all make more use of sensors. Costs for farmers will decrease, and working conditions in the fields and stalls will get better. Autonomous vehicles with actual eyesight will be outfitted with new lidar devices. Handling the heterogeneity and complexity of sensor data, which can have varying formats, resolutions, sample rates, coordinate systems, and error models, is one of the major issues. AI will surpass human power in ways that are unimaginable, changing the face of the planet. In some aspects, it will still fall behind human skills. Its capacity to examine enormous volumes of data, spot trends, and come to well-informed conclusions has created new avenues for growth and increased efficiency. The predictive power of AI will grow dramatically. AI systems will be able to provide extremely accurate forecasts in a variety of industries, including banking, weather, and even medical diagnosis, thanks to their massive data access and sophisticated algorithms.

AI is used to process data from sensors, including temperature, CO2, and motion sensors, humidity meters, and humidity sensors, in order to regulate smart devices and enhance home comfort. AI won't completely take the position of radiologists. It will, nevertheless, alter the way they operate. Radiologists will have to learn ways to collaborate with AI and adjust to these changes. The enhancement in image quality is among the most noteworthy features. By learning to recognize minute patterns and irregularities that are imperceptible to the human eye, artificial intelligence systems are able to evaluate enormous volumes of imaging data. Wearable sensors and artificial intelligence are two more biosensing technological advancements that aim to customize precision medicine for better medical care. These domains provide enhanced patient data collection and analysis through the amalgamation of biosensors with traditional algorithms and pattern recognition. Artificial Intelligence is anticipated to enhance sectors such as healthcare, manufacturing, and customer service, resulting in better experiences for employees and clients. It does, however, confront difficulties including more regulations, issues about data protection, and concerns about employment losses. Contributions are invited from diverse disciplines and perspectives, focusing on the transformative potential and future advancements of AI in multi-sensor imaging and data fusion.

2) The aim and scope of the Special Issue shall be highlighted.

The aim and scope of the special issue focus on exploring the innovative integration of artificial intelligence with multi-sensor imaging and data fusion technologies across various sectors such as healthcare, agriculture, autonomous systems, and smart environments. It seeks to present cutting-edge advancements in AI-driven sensor fusion techniques, addressing challenges like heterogeneous sensor data, edge computing balance, real-time analysis, and privacy concerns. Contributions that demonstrate novel AI applications in precision medicine, smart agriculture, autonomous vehicle perception, wearable biosensing, predictive analytics, and secure sensor networks are especially encouraged. The special issue aims to highlight interdisciplinary research that advances efficient, intelligent multi-sensor data processing to improve decision-making, productivity, and quality of life.

3) Suggested themes shall be listed.

Models of Deep Learning for Fusion of Multisensor Data.

Multi-sensor systems using AI-driven image registration.

AI Methods for Multi-Sensor Fusion in Autonomous Systems include Real-Time Applications.

Multispectral and Hyperspectral Image Fusion Enhanced by AI.

AI and Medical Imaging for Integration of Multimodal Data.

AI and Edge Processing for Multi-Sensor Fusion.

AI for Remote Sensing Multi-Sensor Fusion.

Sturdy AI Algorithms for Fusion in Unfavorable Conditions.

Intelligent Surveillance Systems using AI Enhanced Sensor Fusion.

Fusion of Multiple Sensor Data for AI-Powered Predictive Maintenance.

Augmented Human Machine Interaction with AI and Sensor Fusion.