Wireless Sensor Networks (WSNs) have been spoken of since 2003 and in truth would have been expected to be more pervasive in 2009 than is currently the case. However, with initiatives  throughout the world for smart infrastructure and smart cities it is reasonable to assert that WSNs will be a key technology driver for these initiatives. Energy saving programs, environmental considerations and the growing presence of what can be termed the 'Green' movement have created opportunities for WSN solutions in commercial buildings and in industries such as oil and gas and healthcare.

The capabilities of WSNs can be divided into that of measurement and detection. Examples of the former would be the recording of temperature, humidity and rainfall in a physical environment while intrusion detection and the detection of the presence of chemicals would be examples of the latter. It is the latter category which frequently requires more advanced capabilities than has been traditionally offered and in many instances requires a wireless sensor to have multimedia capabilties. The term 'Wireless Multimedia Sensor Networks' (WMSNs) appears to have been first coined by the Broadband Wireless Networking Lab at the Georgia Insitute of Technology (See http://www.ece.gatech.edu/research/labs/bwn/WMSN/). In essence, a WMSN is a network of wireless interconnected smart objects that can record multimedia content such as video and audio streams, images and scalar data from an environment.

The expansion of wireless sensors for the detection of multimedia content provides a richer realm of capabilities for WSNs. A WMSN can perform surveillance through the deployment of video and audio sensors to monitor an environment such as a public event or a private facility. Car traffic can be monitored to offer smart traffic routing advice to avoid congestion. Medical sensors can be integrated with 3G multimedia telecommunications networks to enable the monitoring of blood pressurce, breathing etc. of infirm or elderly patients while Machine Vision Systems (i.e. a system that can understand what is perceived visually) can be integrated with WMSNs to facilitate visual inspections and automated magnification for industrial process control.

To create a multimedia wireless sensor an audio and/or visual data collection module must be attached to a low-power wireless transceiver that is capable of processing and transmitting sensing video signals. Fortunately, hardware such as CMOS (Complementary Metal-Oxide Semiconductor) cameras and microphones have fallen in price in recent years to enable the creation of wireless sensors. A CMOS camera uses a CMOS-based image sensor chip which means that all required camera circuits can be integrated onto the same chip which in turn makes it possible to attach small cameras to constrained devices such as wireless sensors. This integration of video and audio technology with sensor networks enables the latter to provide richer content that was not feasible with the first wave of wireless sensors as audio, video, images, text and sensor signals can all be recorded and disseminated by a single WSN to provide a comprehensive analysis of a monitored environment. Using Vertoda, real-time analysis and interpretation of a situation can be performed and distributed to the rest of an organisation's software and systems.

There are a number of challenges that must be considered when discussing WMSNs. Multimedia content has a high bandwidth requirement which means that a multimedia sensor should have a high rate of data transmission. Power consumption is another key challenge. Multimedia data requires not only high transmission rates but also extensive processing. This is potentially a severe drain on the battery life of a multimedia sensor so protocols, algorithms and architectures must be designed with this challenge in mind.

Once the challenges of multimedia content recording are overcome, WMSNs can greatly enhance the capabilities of WSNs and open up new and complementary applications for diverse smart cities and smart infrastructure. There are however two other technologies that potentially complement WSNs and these must also be examined - GPS (Global Positioning System) and RFID (Radio Frequency Identification).

Given the diverse applications and the ad-hoc and frequently mobile nature of WSNs (for example, in emergency response situations) GPS would appear to be a natural complementary technology for integration within a WSN. GPS is integrated in sensor offerings by companies such as Crossbow (http://www.xbow.com). WSNs can be GPS-enabled by using GPS-enabled motes i.e. a GPS receiver attached to a wireless transceiver. This enables each node to be aware of its position relative to the network. However, making every sensor within a WSN GPS-enabled is not a cost-effective solution and may  be impractical in enclosed spaces. For this reason, a number of GPS-free solutions have been proposed. In general, these alogorithms provide direction node localization based on the relative motion of neighbouring motes or the distances in the number of hops between nodes which thus obviates the need for GPS infrastructure.

Surprisingly, given that RFID and WSNs both fall under the branch of Computer Networking known as Pervasive Computing, relatively few attempts have been made to integrate the two technologies. In essence, RFID is a means of storing and retrieving data through electromagnetic transmission to an RF (Radio Frequency) compatible integrated circuit. It is typically used to label and track items in supermarkets and warehouses. Wal-Mart and Tesco, among many others, use RFID systems for management of their supply chains.

RFID tags can be categories as active, passive and semi-passive (or indeed, semi-active) tags. An active tag has a battery-powered radio transceiver whereas a passive tag operates without any battery. The latter achieves this by reflecting the RF signal transmitted to it from a reader or transceiver and adds its own data to the signal. Similarly, semi-passive tags use the radio waves of other senders as the energy source for transmitting their data. Unlike passive tags, however, semi-passive tags may have batteries to maintain memory or power other functions. It is not surprising to note that active tags are the most powerful RFID tags available given their larger range, memory and functionality but are also more expensive.

Sensing capabilities can be added to RFID tags using the same RFID protocols for reading the tag's ID. Tags will either have integrated sensors or will allow for adding additional sensors. A number of vendors are offering RFID tags with sensing capability. RFID and wireless sensors are natural complements for supply chain applications as the latter can be used for monitoring temperature in the chill chain and other situations where the recording of environmental conditions is imperative for the preservation of the goods being transported.

RFID readers can also be combined with an RF transceiver. Such a wireless device can sense environmental conditions and read IDs from tagged objects as well as transmitting this information to a data capture portal such as Vertoda. The integration of RFID into an ad-hoc WSN opens up many new applications. For example, a healthcare system that leverages RFID and wireless sensor technologies can monitor not only the patient's vital signs but also their medicine and pill bottles to track when a bottle is removed or replaced by a patient. Automated asset tracking and inventory management would also be facilitated by combining these two technologies.

We have referred to the use of WSNs for medical monitoring applications. WSNs that record conditions in the human body are commonly referred to as Wireless Biosensor Networks. In addition to monitoring the body, WSNs can also be secured using fingerprints or retina scans.  The use of biometrics in WSNs is something we will explore in a coming blog.

WSNs have many diverse applications. However, it is only through the integration of WSNs with multimedia, GPS and RFID that WSNs can offer a comprehensive solution to meet all tracking and monitoring needs for smart cities and smart infrastructure.