Are you thinking of a new direction for your research groups or something to add or expand what you are currently doing? We have got some things for you to ponder about.
Unmanned Autonomous Aerial Vehicle Technologies Using WSN
Experimental hands-on research on hardware-in-the-loop embedded electronic systems for unmanned autonomous aerial vehicle technologies can be conducted using your practical WSN hardware embedded electronics skills. Integrating commercially available hardware to create a fully autonomous gimbaled sensor platform rig that could be mounted onboard generic small scale Unmanned Aerial Vehicles in order to interface at the guidance level with the onboard flight control system, thereby enabling sensor information to be used intelligently to instruct the Unmanned Aerial Vehicle where it needs to go and where it needs to point the onboard sensor.
Infrastructures for energy data collection and analysis in networked manufacturing plants using WSN
Regardless of the field of study or preference for defining data either quantitatively or, qualitatively, accurate data collection is essential to maintaining the integrity of manufacturing plants. Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of errors occurring and could avert the dangers often encounter at the plants. There is the potential to cause disproportionate harm when these research results are used to support public policy recommendations. WSN can be use in preserving data integrity is to support the detection of errors in the data collection process, whether they are made intentionally or deliberate falsifications or not whether the errors occur as systematic or random errors.
3D visualization of Sensor Networks and Applications
The goal of this research will be to analyse the implications of the sensing and communication ranges on coverage and connectivity. This should be focus to tackle practical deployment in oil and gas industry, and underwater surveillance. Enabling new Approaches to Mitigate Gravity Segregation of CO2 .Thus,using sensoric imaging applications running with mobile sensors for monitoring and surveillance of CO2 in thick reservoirs, flood front movement and excess reaction of CO2. The images should be created with massive visualization 3D techniques with an In-situ sensing that should produce detail description and detection of CO2 Plume and Flood-Gravity Override with WSN approach
There is need to have a generally acceptable simulator that will give room for performance metrics and energy consumption. Such a frame work would need to be based on application modeling and verified by extensive testing. The simulator could be used to explore further interactions between applications and the TCP layer. This offers the possibility that future real-time, interactive nodes could adapt the information they send as a function of variability and network congestion. Such cases will exploit knowledge of prior path characteristics to increase performance and network safety.
Satellite-WSN routing Technology
The current tools for simulation produces have error rate and a limitation in buffering. There is need for extra work to be done to check the heterogeneous capabilities of the network and to verify the multi-path and asymmetrical load balancing. Other future challenges includes ability to transfer data with satellite advantages with the IP stack in WSN nodes, ability to also used the satellite to change the routing mechanism using the generated IP address.
Sensors to Control Crystallization of Pharmaceuticals and Fine Chemicals
Intelligent decision control and support can be made using wireless sensor in pharmaceutical and chemical industries. The research should aim at creating a comprehensive intelligent decision support (IDS) and control platform for continuous manufacturing comprising monitoring, signal processing, data analysis, communications and control technologies. The key challenge of real time, robust monitoring of quantitative particle attributes is crucial for the downstream processing of particulate products. No current solution allows the processing of data from in-line sensors to reliably extract these attributes in real time across multiple manufacturing steps and the subsequent use of this knowledge for IDS and control of manufacturing processes. Current measurement techniques only yield limited information on particle shape and size; the innovative multi-signal analysis approach will enable unprecedented control over critical quality attributes e.g. to control a mean particle size of 100 micron and achieve this reliably.
Crowd as a Sensor
Social media is a comprehensive source of all kinds of information. Twitter users provide us with the latest news, Flickr users enable us to see some nice pictures from their holidays and Foursquare users tell us where we can find the place to be. Social networks are so rich in detailed information, because people tend to report about (often unusual) experiences they make in their immediate environment. Additionally, using mobile smartphones enables them augmenting those datasets with geospatial information derived from GPS receivers. Thus social media users provide us with information about WHAT is going on WHERE in REAL-TIME. This fact allows leveraging social media as a distributed wireless sensor network. Social media captures real-world events. It is obvious that this digital image of reality should also reflect real-world scale levels. However, less is known about the relationship of scale and crowdsourced geographic information. We don’t know which layers of interwoven scale levels we can find. We don’t even have suitable tools for scale-dependent analyses of social media data. Therefore, one essential part of the “Crowd as a Sensor” project is to investigate the influence and analysis of (primarily geometric) scale on this very unique kind of data. Another fascinating idea is to combine research fields that are typically decoupled from each other: Geospatial techniques and computational linguistics. Incorporating textual semantics with geographic analyses is very beneficial. Both fields can strongly benefit from each other. Thus, the second big part of the project aims to investigate methods that combine geospatial / geostatistical methods with those from computational linguistics. This will geo-enable computational linguistics and bring more persuasive meaning to geospatial analyses.
Review of Energy Optimization In Heterogeneous Networks
In wireless sensor networks energy consumption is a key issue for the sensor lifetime and accuracy of information transmitted and received. Protocols and mechanisms have been proposed for energy optimization considering various communication factors and types of applications. Conserving energy and optimizing energy consumption are challenges in wireless sensor networks, requiring energy-adaptive protocols, self-organization, and balanced forwarding mechanisms. This research will compare energy models and make a Novel proposal on the best approach for energy optimization particularly in heterogeneous networks that may lack continuous network connectivity.