I think this is an open-ended question. You would need to identify the aspect of WSN research (i.e., security, routing, energy efficiency, reliability, scalability, etc) that interests you. Once that is done you can now receive targeted answers in that regard. All these areas have exciting problems that can be identified for further research.
The WSN with dynamic agents is relatively new topic in WSN. Secondly, as many cpuputing devices such as mobile, consist of multiple sensors, the gap between MANET and WSN has reduced and therefore most of the challanges related to MANET are also applicable to WSN.
WSN for medical health care application also have few additional challanges than the traditional WSN. Finally, Multimedia sensor network have QoS requirement on top of energy saving requiremtns.
No, this is a very old topic. There are hundreds of papers on indoor localization techniques. Frankly speaking, this field is very saturated and its quite difficult to do some extra ordinary work, unless you focus on the hardware aspects. If still interested, you can explore the usage of WSNs in healthcare and smart cities.
Data Collection using mobile sink, Sensor's Battery recharge using mobile Wireless Recharger, 3D Scenarios simulation, Energy Harvesting these are some hot research topics in WSN.
I think this is an open-ended question. You would need to identify the aspect of WSN research (i.e., security, routing, energy efficiency, reliability, scalability, etc) that interests you. Once that is done you can now receive targeted answers in that regard. All these areas have exciting problems that can be identified for further research.
I believe that applied WSN for Smart Cities and Industry 4.0 will be a trend for at least the next 10 years. I mean that many technological issues about WSN operation are already solved and what we are expecting now is increasing practical exploitation to achieve the expected benefits of such networks.
In the current scenario, research in the WSN domain can be classified into two major streams:
(i) Core: networking, protocol design, deployment strategy, green communication, etc.
(ii) Inferential: Data harvesting, context inferences, decision-making, data analysis, edge AI, etc.
The latter thrives various application domains, such as Smart Cities, Smart Healthcare, Smart Home, Smart Farming, Smart Agriculture, Industry 4.0/5.0, Intelligent Transportation System, etc. It fulfils the requirements of the modern era of IoT, which is driven by data. In today's scenario, data is an asset but turning data into an insightful knowledge with minimum overhead and minimum complexity, especially in WSN-led IoT applications, is a challenge. In recent years, the focus of research in WSN domain has shifted towards edge computing-based techniques and Edge AI to achieve a trade-off between challenges of the resource-constrained environment and utilization/processing of the sensed data to automate the operations with the effective decision-making in near real-time.