Wireless sensor networks for micro climate monitoring

rameshbala

Reputable
May 10, 2014
1
0
4,510
Environmental monitoring has a long history. In early times analog mechanisms were used to measure physical environmental parameters. Some of them with the ability to record the values on paper dish. The old mechanisms recorded data at specific intervals and required human intervention to download them. Some years ago, digital data loggers have replaced the old mechanical. The digital data loggers are more easy to operate and to maintain and cheaper than the old mechanisms. Digital data loggers may also be combined with long-range communication networks, such as GSM, to retrieve data from remote sites. However, digital data loggers have some drawbacks. The digital data loggers solution, usually provide monitoring at one point only and in many cases multiple points need to be monitored. There is not a standard to store data and to communicate with the data logger, so several different solutions are used. Recent advances in micro-electro-mechanical systems and in low-power wireless network technology have created the technical conditions to build multi-functional tiny sensor devices, which can be used to observe and to react according to physical phenomena of their surrounding environment [1]. Wireless sensor nodes are low-power devices equipped with processor, storage, a power supply, a transceiver, one or more sensors and, in some cases, with an actuator. Several types of sensors can be attached to wireless sensor nodes, such as chemical, optical, thermal and biological. These wireless sensor devices are small and they are cheaper than the regular sensor devices. The wireless sensor devices can automatically organize themselves to form an ad-hoc multi hop network. Wireless Sensor Systems (WSSs), may be comprised by hundreds or maybe thousands of ad-hoc sensor node devices, working together to accomplish a common task. Self-organizing, self-optimizing and fault-tolerant are the main characteristics of this type of network [2]. Widespread networks of inexpensive wireless sensor devices offer a substantial opportunity to monitor more accurately the surrounding physical phenomena’s when compared to traditional sensing methods [3]. Wireless sensor network has its own design and resource constrains [4]. Design constrains are related with the purpose and the characteristics of the installation environment. The environment determines the size of the network, the deployment method and the network topology. Resources constrains are imposed by the limited amount of energy, small communication range, low throughput and reduced storage and computing resources. Research efforts have been done to address the above constrains by introducing new design methodologies and creating or improve existing protocols and applications [1, 2]. It provides a review on Wireless Sensor Systems solutions to environmental monitoring applications. The remainder of this paper is organized as follows. Section II gives an overview of sensor network platforms. Section III analyses the standard IEEE 802.15.4 [5] while Section IV overviews recent sensor architectures. WSS environmental monitoring projects are presented in Section V and challenges related with environment sensor networks are studied in Section VI. Section VI concludes the paper and addresses future research challenges related to WSS networks deployment.








2.1 Introduction
Wireless sensor challenges that have limited resource capabilities of the hardware i.e., memory, processing power, bandwidth and energy deposits. Much research is currently being conducted in the areas like: improving reliability of data transfer; Finding solutions to assist easy deployment and maintenance; developing techniques that will enforce secure, private and trustworthy networks.

2.2 Environmental monitoring
Sensor networks is a technology that gained momentum over the recent years and it is very promising in making the vision of Mark Weiser a reality: “Conceive a new way of thinking about computers in the world, one that takes into account the natural human environment and allows computers themselves to vanish into the background” [15]. Fortunately for researchers, this new technology brings up a wealth of research problems that need to be solved. Such networks are considerably different from the traditional computer networks we have been building over the past years, and thus they may have different requirements and/or constraints in each of the seven OSI layers [2].
Sensor networks have two significant differences from traditional networks, namely nodes have limited processing capability and power and a sensor network may consist of a huge number of nodes. As a result, the traditional layer architecture may not be appropriate since it is designed to support generality, rather than simplicity. As a result, a new architecture is needed which will also help us handle the huge volume of measurement data that the network can generate. Furthermore, it is necessary to find an efficient way of processing the data (preferably in a decentralized manner) and turn them into meaningful information that the user can be benefit from.

2.3 Challenges For Environmental Sensor networks
The term Internet of Things [36] describes a vision in which networks and embedded devices are omnipresent in our lives and provide relevant content and information whatever the user location. Sensors and actuators will play a relevant role to accomplish this vision. Although, extensive efforts have been done to achieve the Internet of Things vision, there still some challenges that need to be addressed. The most relevant are presented bellow.
Power management
This is essential for long-term operation, especially when it is needed to monitoring remote and hostile environments. Harvesting schemes, cross-layer protocols and new power storage devices are presented as possible solutions to increase the sensors lifetime.
Scalability
A wireless sensor network can accommodate thousands nodes. Current real WSS for environment proposes the use of tens to hundreds nodes. So it is necessary to prove that the available theoretical solutions are suited to large real WSS.
Remote management
Systems installed on isolated locations cannot be visited regularly, so a remote access standard protocol is necessary to operate, to manage, to reprogramming and to configure the WSS, regardless of manufacturer.


2.4 End – To - End Software Solution

Our end-to-end WSS software solution has evolved to conveniently present data to the end user (the ultimate purpose of a WSS) and to automate recurring tasks that are common to all deployments. It is the culmination of our numerous real-world deployment experiences, mainly outdoor solar-powered deployments, and substantial software development effort. It comprises a comprehensive suite of back-end tools and a generic sensor-node application to Sense.
The architecture of our end-to-end system is illustrated in Fig. 8 for the case of deployment E. Our back-end toolset consists of software that manages sensor data at the network gateway level, a central relational database, a web portal (Fig. 9) for data visualization, and a collection of Python utilities to remotely control and monitor deployed nodes and networks. Automated monitoring utilities detect hardware failures and alert relevant personnel. Data retrieval and visualization tools allow slow degradations in transducer performance or battery capacity to be detected and rectified. Data can be queried directly from nodes [41] but our focus was on providing the greatest flexibility across a wide range of application domains, and this was the basis for our decision to use a central database for data management.



To Sense runs under FOS, uses the low-power MAC and LQ routing, and provides functionality for sensor management (add, remove, re-task, etc.), as well as interrogation of node health using remote procedure calls. This is another example of increasing functional abstraction for WSSs and is enabled by the underlying software tools. The ability to query the health of individual nodes is crucial to discover. Data flow in and out of the WSS and interaction with the back-end Python tools.

Environmental monitoring has a long history. In early times analog mechanisms were used to measure physical environmental parameters. Some of them with the ability to record the values on paper dish. The old mechanisms recorded data at specific intervals and required human intervention to download them. Some years ago, digital data loggers have replaced the old mechanical. The digital data loggers are more easy to operate and to maintain and cheaper than the old mechanisms. Digital data loggers may also be combined with long-range communication networks, such as GSM, to retrieve data from remote sites. However, digital data loggers have some drawbacks. The digital data loggers solution, usually provide monitoring at one point only and in many cases multiple points need to be monitored. There is not a standard to store data and to communicate with the data logger, so several different solutions are used. Recent advances in micro-electro-mechanical systems and in low-power wireless network technology have created the technical conditions to build multi-functional tiny sensor devices, which can be used to observe and to react according to physical phenomena of their surrounding environment [1]. Wireless sensor nodes are low-power devices equipped with processor, storage, a power supply, a transceiver, one or more sensors and, in some cases, with an actuator. Several types of sensors can be attached to wireless sensor nodes, such as chemical, optical, thermal and biological. These wireless sensor devices are small and they are cheaper than the regular sensor devices. The wireless sensor devices can automatically organize themselves to form an ad-hoc multi hop network. Wireless Sensor Systems (WSSs), may be comprised by hundreds or maybe thousands of ad-hoc sensor node devices, working together to accomplish a common task. Self-organizing, self-optimizing and fault-tolerant are the main characteristics of this type of network [2]. Widespread networks of inexpensive wireless sensor devices offer a substantial opportunity to monitor more accurately the surrounding physical phenomena’s when compared to traditional sensing methods [3]. Wireless sensor network has its own design and resource constrains [4]. Design constrains are related with the purpose and the characteristics of the installation environment. The environment determines the size of the network, the deployment method and the network topology. Resources constrains are imposed by the limited amount of energy, small communication range, low throughput and reduced storage and computing resources. Research efforts have been done to address the above constrains by introducing new design methodologies and creating or improve existing protocols and applications [1, 2]. It provides a review on Wireless Sensor Systems solutions to environmental monitoring applications. The remainder of this paper is organized as follows. Section II gives an overview of sensor network platforms. Section III analyses the standard IEEE 802.15.4 [5] while Section IV overviews recent sensor architectures. WSS environmental monitoring projects are presented in Section V and challenges related with environment sensor networks are studied in Section VI. Section VI concludes the paper and addresses future research challenges related to WSS networks deployment.

SURVEY
2.1 Introduction
Wireless sensor challenges that have limited resource capabilities of the hardware i.e., memory, processing power, bandwidth and energy deposits. Much research is currently being conducted in the areas like: improving reliability of data transfer; Finding solutions to assist easy deployment and maintenance; developing techniques that will enforce secure, private and trustworthy networks.

2.2 Environmental monitoring
Sensor networks is a technology that gained momentum over the recent years and it is very promising in making the vision of Mark Weiser a reality: “Conceive a new way of thinking about computers in the world, one that takes into account the natural human environment and allows computers themselves to vanish into the background” [15]. Fortunately for researchers, this new technology brings up a wealth of research problems that need to be solved. Such networks are considerably different from the traditional computer networks we have been building over the past years, and thus they may have different requirements and/or constraints in each of the seven OSI layers [2].
Sensor networks have two significant differences from traditional networks, namely nodes have limited processing capability and power and a sensor network may consist of a huge number of nodes. As a result, the traditional layer architecture may not be appropriate since it is designed to support generality, rather than simplicity. As a result, a new architecture is needed which will also help us handle the huge volume of measurement data that the network can generate. Furthermore, it is necessary to find an efficient way of processing the data (preferably in a decentralized manner) and turn them into meaningful information that the user can be benefit from.

2.3 Challenges For Environmental Sensor networks
The term Internet of Things [36] describes a vision in which networks and embedded devices are omnipresent in our lives and provide relevant content and information whatever the user location. Sensors and actuators will play a relevant role to accomplish this vision. Although, extensive efforts have been done to achieve the Internet of Things vision, there still some challenges that need to be addressed. The most relevant are presented bellow.
Power management
This is essential for long-term operation, especially when it is needed to monitoring remote and hostile environments. Harvesting schemes, cross-layer protocols and new power storage devices are presented as possible solutions to increase the sensors lifetime.
Scalability
A wireless sensor network can accommodate thousands nodes. Current real WSS for environment proposes the use of tens to hundreds nodes. So it is necessary to prove that the available theoretical solutions are suited to large real WSS.
Remote management
Systems installed on isolated locations cannot be visited regularly, so a remote access standard protocol is necessary to operate, to manage, to reprogramming and to configure the WSS, regardless of manufacturer.


2.4 End – To - End Software Solution

Our end-to-end WSS software solution has evolved to conveniently present data to the end user (the ultimate purpose of a WSS) and to automate recurring tasks that are common to all deployments. It is the culmination of our numerous real-world deployment experiences, mainly outdoor solar-powered deployments, and substantial software development effort. It comprises a comprehensive suite of back-end tools and a generic sensor-node application to Sense.
The architecture of our end-to-end system is illustrated in Fig. 8 for the case of deployment E. Our back-end toolset consists of software that manages sensor data at the network gateway level, a central relational database, a web portal (Fig. 9) for data visualization, and a collection of Python utilities to remotely control and monitor deployed nodes and networks. Automated monitoring utilities detect hardware failures and alert relevant personnel. Data retrieval and visualization tools allow slow degradations in transducer performance or battery capacity to be detected and rectified. Data can be queried directly from nodes [41] but our focus was on providing the greatest flexibility across a wide range of application domains, and this was the basis for our decision to use a central database for data management.



To Sense runs under FOS, uses the low-power MAC and LQ routing, and provides functionality for sensor management (add, remove, re-task, etc.), as well as interrogation of node health using remote procedure calls. This is another example of increasing functional abstraction for WSSs and is enabled by the underlying software tools. The ability to query the health of individual nodes is crucial to discover. Data flow in and out of the WSS and interaction with the back-end Python tools.