Multi sensors and smart technologies have benefited every field where they have been used. Sensors are devices that detect and gather signals from a variety of sources that can be used, including light, temperature, movement, and pressure. The applications of integrative sensors are not only limited to healthcare, agriculture, lifestyle, aerospace, or autonomous vehicles, the word ‘environment’ refers to the physical spaces in our surroundings in all diversity. The goal of Developing Intelligent Environments (DIE) is to improve the user experience, better manage the environment, and raise user awareness of it. From the standpoint of computing science, DIE must make use of a diverse set of small, distributed sensing or computational nodes to detect and deliver personalized services to users while they interact and exchange data with the environment. These new integrated sensor techniques are necessary for communicating with users, perceiving and comprehending the world, building living places, and coexisting with artificial agents. DIE represents a transition from massive mainframes to pervasive computers, as well as a transformation from many users using a single computer to embedded computers, due to multi-sensor fabrication techniques and sensors miniaturization.

Pervasive computing is seen as the next wave in the evolution of mainframe technology. The study of DIEs, on the other hand, necessitates a more advanced approach due to the multiple development axes that led to the applications for engineering, healthcare, environment inspection, and monitoring. Dependability, security, comfort, performance, proactiveness, knowledge, and size are the factors that must be considered for developing an intelligent environment. Reliable intelligent technologies are widely required in various developing environments such as emerging signal conditioning ICs, feature extraction, edge computing, coupling, and communications. DIE has a wide range of applications, including health informatics, artificial intelligence, digital twins, IoTs, and energy management.

This Special Issue aims to bring original research and review articles with a focus on developing reliable intelligent environments using novel multimodal sensors. Submissions can also discuss new materials and new techniques for integrated sensors fabrication, selection, and fusion.

Potential topics include but are not limited to the following:

• Design, modeling, and evaluation of integrative sensors
• Novel sensor fabrication techniques, for example MEMS, printing, coating, and films
• Multi sensors in Industry 4.0 and Digital Twin
• RFID multimodal sensors and wireless coupling
• Coupling and communication between sensors
• Emerging signal conditioning techniques for multi-sensors
• Integrated signal conditioning for real-world sensors
• Sensor signal processing methods for high precision and stability
• Integrated feature extraction and pattern recognition
• Multi-sensor feature extraction and data fusion
• Sensor simulation and modeling
• Software engineering techniques for developing intelligent environments
• Artificial Intelligence-based sensors for next-generation IoT
• Explainable AI (XAI) for smart sensors
• Intelligent and reliable healthcare services using multi-sensors