Wireless Sensor Networks (WSNs) are essential components of modern
information systems because they promote efficient gathering and sharing of
information across a variety of domains, such as smart cities, healthcare, and
environmental monitoring [1]. Yet, the sensor node's resource limitations, such as
energy and storage, largely inhibit real-time accuracy, safety, and scalability. To
resolve these challenges, this study examines how existing mechanisms of computing,
namely, Artificial Intelligence (AI) and Quantum Computing (QC), may be integrated
in wireless networks. The present chapter tries to present a detailed analysis of how QC
and AI technologies can enhance WSN performance, security, and efficiency.
Predictive maintenance and energy-efficient data transmission have all been
investigated through Artificial Intelligence (AI) methods such as Machine Learning
(ML) and Deep Learning (DL). Through the help of post-quantum cryptography and
quantum algorithms in order to achieve resource optimisation and routing, the work
also considers how QC can be employed for security issues. The key findings indicate
that although AI provides intelligent, low-latency processing, QC gives strong
cryptographic frameworks and optimisation facilities. Notwithstanding these
improvements, there are still issues of implementation complexity, scalability, and
hardware constraints. Besides outlining future areas of research, including Intelligencebased optimisation models, scalable quantum-secure communication protocols, and the
design of intelligent, autonomous sensor networks, the current research highlights the
revolutionary possibility of combining AI and QC in WSNs. This review focuses on
the revolutionary potential of integrating AI and QC in WSNs and proposes future
research areas, such as AI-based optimisation models, scalable quantum-secure
communication protocols.
Keywords: AI-enhanced sensor networks, Big data analytics, Data privacy, Edge computing, Energy efficiency, Internet of things (IoT), Quantum algorithms, Quantum computing, Quantum machine learning (QML), Real-time data Processing, Sensor nodes, Sensor networks, Smart cities, Wireless communication, Wireless sensor network security.
