In order to support M2M applications, mobile cellular networks and wireless sensor networks (WSN) are evolving from heterogeneous networks to converged networks. Distinguished from cellular systems, WSNs have a denser level of node deployment and higher unreliability of sensor nodes. They have severe energy, computation, and storage constraints. The key disadvantages include less mobility robustness, small coverage, and weak terminals. In contrast, cellular networks have the advantages of mobility robustness, large coverage, and powerful user terminals, but their deployment and management are expensive and complicated. Therefore, it is intuitive to integrate cellular networks and WSNs for supporting M2M communications. The convergence of cellular networks and WSNs is supposed to benefit both types of networks. For WSN, cellular networks can enable higher layer control and optimization to prolong network life time, improve WSN system performance, and provide quality of service (QoS). For cellular networks, WSN can enable the cognitive and intelligent aspects of the cellular system. It is envisaged that the converged network architecture of cellular networks and WSN could enable better wireless services and more data-centric applications.

There are a number of standardization bodies in the field of WSNs and several of them are currently either ratified or under development. The IEEE focuses on the physical and MAC layers; the Internet Engineering Task Force (IETF) works on layers 3 and above. In addition to these, bodies such as the International Society of Automation (ISA)provide vertical solutions, covering all protocol layers. There are also several non-standard, proprietary mechanisms and specifications.

IEEE 1451. A set of smart transducer interface standards developed by the IEEE Instrumentation and Measurement Society's Sensor Technology Technical Committee that describes a set of open, common, network-independent communication interfaces for connecting transducers to microprocessors, instrumentation systems, and control/field networks. The goal of the IEEE 1451 family of standards is to allow the access of transducer data through a common set of interfaces whether the transducers are connected to systems or networks via a wired or wireless means.

IEEE 802.15.4. Is the basis for the ZigBee, ISA100.11a, WirelessHART, and MiWi specifications, each of which further extends the standard by developing the upper layers which are not defined by 802.15.4. Alternatively, it can be used with 6LoWPAN and standard Internet protocols to build a wireless embedded Internet. Now the emphasis is on low-cost communication of nearby devices with little to no underlying infrastructure, intending to exploit this to lower power consumption even more. Its important features include real-time suitability by reservation of guaranteed time slots, collision avoidance through CSMA/CA, and integrated support for secure communications. The devices also include power management functions such as link quality and energy detection.

ZigBee. The technology defined by the ZigBee specification is intended to be simpler and less expensive than other WPANs, such as Bluetooth. ZigBee is targeted for radio-frequency (RF) applications that require a low data rate, long battery life, and secure networking. The low cost allows the technology to be widely deployed in wireless control and monitoring applications.

Low power usage allows longer life with smaller batteries. Mesh networking provides high reliability and more extensive range.

ISA100.11a. Is an open wireless networking technology standard developed by the ISA for wireless industrial networks. The standard specifies how communication between devices is established and how the wireless infrastructure can be used to run industrial control applications. The ISA 100.11a standard specifies different functional roles for various operations needed to run and manage a wireless industrial network.

WirelessHART. At the very bottom, it adopts IEEE 802.15.4-2006 as the physical layer. On top of that, WirelessHART defines its own time-synchronized MAC layer. Some notable features of WirelessHART MAC include strict 10 min time slot, network-wide time synchronization, channel hopping, channel blacklisting, and industry standard AES-128 ciphers and keys. The network layer supports self-organizing and self-healing mesh networking techniques.

MiWi Protocol. Designed for low data transmission rates, short distance, and cost constrained networks, such as industrial monitoring and control, home and building automation, remote control, low-power wireless sensors, lighting control, and automated meter reading, the protocol provides features to find form and join a network, as well as discovering nodes on the network en route to them.

6LoWPAN. This is a set of standards defined by the IETF, which creates and maintains all core Internet standards and architecture work. 6LoWPAN standards enable the efficient use of IPv6 over low-power, low-rate wireless networks on simple embedded devices through an adaptation layer and the optimization of related protocols. Recent activities related to 6LoWPAN include the IP for smart objects (IPSO) to promote the use of IP in smart devices and Internet of things business.

Current and Potential Applications

Military sensing, physical security, air traffic control, traffic surveillance, video surveillance, industrial and manufacturing automation, distributed robotics, environment monitoring, and building and structures monitoring are few of the current and potential applications of sensor networks. The sensors in these applications may be small or large, and the networks may be wired or wireless. Since mobile wireless sensor networks are a relatively new concept, its specific, unique application areas are yet to be clearly defined. Most of its application scenarios are the same as that of traditional wireless sensor networks, with the only difference of mobility of mobile sink, preferably in the form of mobile phones.

Smart transport system. A network of sensor setup on a vehicle can interact with its surroundings to provide valuable feedback on local roads, weather, and traffic conditions to the driver, enabling adaptive drive systems to respond accordingly. A broad city-wide distributed sensor network could be accessed to indicate traffic congestion, administer toll tax, or provide continually updated destination routing feedback to individual vehicles. Condition and event detection sensors can activate systems to maintain driver and passenger comfort and safety through the use of airbags and seatbelt pre-tensioning.

Security. Sensors can be used to implement security system in daily life. On an individual basis, mobile phones can enter into a session with the already present sensors in the area. Mobile-enabled wireless sensor networks can help monitor the environment, both external and internal.

Social interaction. With the possible integration of RFID tags and WSN, mobile phones can act as sinks to have a social interaction among peers who share common interest. Similarly, this combination of RFID tags and WSN can help mobile phone users carry out all their tasks like shopping, billing, information gathering, guidance, and social interaction.

Health. A network of advanced bio-sensors can be developed using nanotechnology to conduct point-of-care testing and diagnosis for a broad variety of conditions. This technology will reduce delays in obtaining test results, thus having a direct bearing on patient recovery rates or even on survival rates.

Smart home/smart office. Smart home environments can provide custom behaviors for a given individual. Sensors can control appliances at home. They provide better lighting and air conditioning in offices.

Water catchments, eco-system, remote sensing in disaster management, military, and agriculture are the other application areas.

Future Trends

The future developments in sensor networks would produce powerful and cost-effective devices, so that they may be used in applications like underwater acoustic sensor systems, sensing-based cyber physical systems, time critical applications, cognitive sensing and spectrum management, and security and privacy management.

Cognitive sensor networks are used for acquiring localized and situated information of the sensing environment by deploying a large number of sensors intelligently. Managing a large number of wireless sensors is a complex task.

One can envision a future in which wireless devices, such as wireless keyboards, powerpoint presenters, cell phone headsets, and health monitoring sensors will be ubiquitous. Pervasiveness of these devices leads to increased interference and congestion within as well as between networks, because of overlapping physical frequencies. A generic solution provided is self-adaptive spectrum management middleware for WSNs, which can be easily integrated with an existing single frequency.

The main obstacle in coordination with other networks is limited energy of sensor nodes. To monitor the WSN, the data produced by sensor nodes should be accessible. This can be done by connecting the WSN with the existing network infrastructure such as global Internet, a local area network, or private Internet.