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With the rapid development of society and the economy, an increasing number of human activities have gradually destroyed the marine environment. Marine environment monitoring is a vital problem and has increasingly attracted a great deal of research and development attention. During the past decade, various marine environment monitoring systems have been developed. The traditional marine environment monitoring system using an oceanographic research vessel is expensive and time-consuming and has a low resolution both in time and space. Wireless Sensor Networks (WSNs) have recently been considered as potentially promising alternatives for monitoring marine environments since they have a number of advantages such as unmanned operation, easy deployment, real-time monitoring, and relatively low cost. This paper provides a comprehensive review of the state-of-the-art technologies in the field of marine environment monitoring using wireless sensor networks. It first describes application areas, a common architecture of WSN-based oceanographic monitoring systems, a general architecture of an oceanographic sensor node, sensing parameters and sensors, and wireless communication technologies. Then, it presents a detailed review of some related projects, systems, techniques, approaches and algorithms. It also discusses challenges and opportunities in the research, development, and deployment of wireless sensor networks for marine environment monitoring.

With the dramatic increase of connected devices, the Internet of things (IoT) paradigm has become an important solution in supporting dense scenarios such as smart cities. The concept of heterogeneous networks (HetNets) has emerged as a viable solution to improving the capacity of cellular networks in such scenarios. However, achieving optimal load balancing is not trivial due to the complexity and dynamics in HetNets. For this reason, we propose a load balancing scheme based on machine learning techniques that uses both unsupervised and supervised methods, as well as a Markov Decision Process (MDP). As a use case, we apply our scheme to enhance the capabilities of an urban IoT network operating under the LoRaWAN standard. The simulation results show that the packet delivery ratio (PDR) is increased when our scheme is utilized in an unbalanced network and, consequently, the energy cost of data delivery is reduced. Furthermore, we demonstrate that better outcomes are attained when some techniques are combined, achieving a PDR improvement of up to about 50% and reducing the energy cost by nearly 20% in a multicell scenario with 5000 devices requesting downlink traffic.

A new orthogonal frequency division multiplexing (OFDM) system embedded with overlay watermarks for location-aware cross-layer design is proposed in this paper. One major advantage of the proposed system is the multiple functionalities the overlay watermark provides, which includes a cross-layer signaling interface, a transceiver identification for position-aware routing, as well as its basic role as a training sequence for channel estimation. Wireless terminals are typically battery powered and have limited wireless communication bandwidth. Therefore, efficient collaborative signal processing algorithms that consume less energy for computation and less bandwidth for communication are needed. Transceiver aware of its location can also improve the routing efficiency by selective flooding or selective forwarding data only in the desired direction, since in most cases the location of a wireless host is unknown. In the proposed OFDM system, location information of a mobile for efficient routing can be easily derived when a unique watermark is associated with each individual transceiver. In addition, cross-layer signaling and other interlayer interactive information can be exchanged with a new data pipe created by modulating the overlay watermarks. We also study the channel estimation and watermark removal techniques at the physical layer for the proposed overlay OFDM. Our channel estimator iteratively estimates the channel impulse response and the combined signal vector from the overlay OFDM signal. Cross-layer design that leads to low-power consumption and more efficient routing is investigated.