Future Trends in Data Fusion for Wireless Sensor Networks
Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 2506
Interests: wireless sensor networks; digital image processing; meta-heuristic techniques
Special Issues, Collections and Topics in MDPI journals
Interests: next-generation networking; blockchain technologies; intrusion detection; network security; cyber security; deep learning; IoT
Special Issues, Collections and Topics in MDPI journals
Interests: impulsive hybrid dynamical systems; biped robots; exoskeleton robots; impacting mechanical systems; chaos and bifurcations theory; chaos control; linear and nonlinear control; linear matrix inequality (LMI); observer design; observer-based feedback control; static output feedback control; active disturbance rejection control
In recent years, technology has grown in an immensely phosphorus way, with sophisticated devices providing a greatly effective acceleration in communication technologies. Wireless sensor networks (WSNs) comprise a wide array of distributed equipment and autonomous devices that can monitor or predict physical and environmental conditions cooperatively. These ever-evolving networks have a wide demand in the current market, taking inputs from smart dust, mobile applications, desktops, as well as clusters. WSNs face many challenges and issues mainly caused by communication failures and the storage of data with computational constraints. These wireless sensor networks are low-powered embedded components implemented for real-time perceiving, producing data to specified targets. WSNs provide an adaptive mechanism for the exhibition of intelligent behaviour through artificial intelligence to solve complex and dynamic problems faced by end users.
WSNs have the flexibility to fetch logs against autonomous users to analyse key issues with the help of topological change, robustness and communication failures. They are considered self-organised and damage-proof in various fields such as agriculture, healthcare, and military and navy aviation.
Researchers have discovered many suitable solutions for communication issue, which is in the beginning stage called the location awareness of WSNs. This location awareness provides a position functionality which is like a global position system (GPS) that is used to fetch the location of users through their current location; through this approach, the user can obtain a high frequency, even indoors. This internally works with multiple algorithms, such as the DV–HOP algorithm, centroid algorithm and ATIP algorithm. It targets the hop distance separating the anchor nodes and target nodes; hence, calculating the overall distance. The reason for using the algorithm inside the sensor networks is that the algorithm has the capability of avoiding errors from any other additional hardwired technologies. Inducing data fusion is the obtainment of a high frequency and the tracking of a user’s location at any time. The main method of using sensor products as a technology with data fusion is sniper detection systems, smart dust, and military applications such as military commands, surveillance, and targeting systems. Since it is a low-cost sensing technology, most of the equipment is covered by the sensing objects. These are also used for much environmental research, such as volcano detection, weather-sensing technologies, early flood detection processed and mainly health applications. The sensor objects included in the data fusion of health applications are often used in artificial retinas, including many other applications. As per the data mining analysis, the data are sent by a signal to the devices and the data fusion acts as an interface by converting the analogy code to digital code, which is then sent to the microcontroller; then, the frequency is given to the radio interface. This Special Issue provides an opportunity for researchers and technologists to promote future research concerning the development of technology for the provision of efficient digital solutions and strategies to combat the current sensing methodologies with the use of data fusion.
Topics of interest include:
- Technological strategies for the effective management of data fusion;
- Role of digital sensing technologies in public health surveillance;
- The role of data fusion systems in managing communication challenges;
- Technological strategies to overcome the conflict issue in sensing applications;
- System model and cluster formation in data fusion;
- Structural architecture to be adapted in WSNs for technical issues;
- Adaptive algorithms used in fusion technologies for WSNs;
- Data transformation on dynamic topologies in mining technologies;
- Level of abstraction in data fusion with source relationship;
- Fusion-based input source relationship in sensor networks;
- Innovative ideas in discussion layers of fusion;
- Sensors, real-time applications, and data fusion in smart dust.
Dr. Manjit Kaur
Dr. Raman Singh
Dr. Hassène Gritli
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