Final Report Summary - CLAP (Cross Layer Algorithms for Phealth)
In most of the developing countries today, often the governments do not have the means to reliable and timely information on the population whereabouts regarding health and the environment especially for the rural areas. On the other hand, as most of the rural areas are either hard-to-reach or technologically lagging, their population cannot get most of the benefits offered by the government. In some cases, rural areas are deprived of good education facilities, health care, food and nutrition, disaster relief etc. Acquiring exact and timely data from these rural areas is a crucial task which could assist the government to extend their development activities as well as to provide the rural areas with the facilities to fulfill the basic needs for living.
Wireless systems could significantly contribute to the development of technologically lagging rural areas especially in the developing countries, in addition to the development of rich and developed areas. In recent years, various wireless technologies have shown promise for a number of public applications, including elevation of quality of life of rural and/or unprivileged population. Such technologies include, among others, wireless ad hoc networks, wireless sensor networks, ubiquitous monitoring, location and experts systems. These technologies offer emerging opportunities that could effectively be used for smartening the environment as well as for improving the socio-economic status of the rural areas in the developing countries.
The Cross Layer Algorithms for PHealth (CLAP) project took into account resent research results in WSN, communication and collaborative environments and resulted in the design of a working prototype, based on the OLPC concept, which measures quality of life parameters. The initial motivation for this project and the main aim for implementing it is to benefit from low-cost, low-power wireless technologies to facilitate bridging the ICT scientific advances and implementation gap in developing countries, by bringing rural areas closer to their government and governments of developing countries closer to the technological level of the developed world in an ICT4D (Information and Communication Technologies for Development) manner.
CLAP carried out a first classification of MAC protocols, cross-layer techniques, cooperative transmission and strategies from previous European projects, standardisation bodies and literature. In parallel, CLAP determined the features of the relevant standards and open literature proposals that must be taken into account in the development of simulators, algorithms and models. The team proceeded to the specification of the architecture and functionality of a WSN, suitable for including cross-layer and cooperative transmission concepts, whereas the services that could be demanded in the next years were defined and a set of QoS requirements was also established. Having identified the initial set of the CLAP cross-layer techniques and cooperative protocols, the proposed architectures and mechanisms were validated.
The conceptualised framework of CLAP consists of four interacting clouds. Wireless sensor networks collect data monitoring QoL parameters, like the environment (water, soil, air, volcano), vital signs, health related human receptors, behavioral patterns. This is referred as cloud A. In this cloud, sensors are deployed in crucial parts of the rural areas, that could range from river banks, geographically challenging parts (for example; hilly areas), schools, gathering places, homes, down to individuals. The sensor networks could collect various critical data (e. g., level of water in the rivers which could help for flood warning, earthquakes etc.) and send them to gateways (sinks is a term widely found in WSN literature as well) referred as cloud B. In our framework a cloud B is implemented by networked communities that pre-exist for some other reason or are formed for this particular case. Examples of such network communities may be found in a OLPC equipped village, a mobile phones carrying community or a hospital on wheels, a vehicle mounted medical facility with wireless access functionality. A cloud B may move around the rural areas and serve many clouds A implementations or may be attached to only one and collect data only from them.
Data communication from a cloud B to the outer world is performed by facilities referred as cloud C. The major task of a cloud C implementation is to ensure reliable acquisition and delivery of data from the rural areas to a centrally located center referred as cloud D. A cloud C facility is capable of (wirelessly) communicating data acting as a repeater or router. It may additionally have capabilities for incoming data to be stored temporarily and/or processed. Examples of cloud C implementations may range from very simple solutions of one single PDA carried by a mailman or a drinking water distributor, to more complex facilities of satellite-linked equipment or vehicle mounted communication amenities.
A cloud D collects (processed or raw) data from cloud B installations communicated through the corresponding cloud C facilities. A cloud D would combine this data with data from other cloud A data and past records for a particular rural area or a number of selected areas and supply it to a referral center (which could also combine decision and action government powers). In this way, the government gets the timely and processed data from the rural areas and decides on the necessary actions accordingly. This data not only helps the government provide various services to rural areas and make educative strategic decisions and planning (as for example by monitoring behavioural patterns and socio-economic indicators), but could also help in emergency situations as well as for prevention (among the many examples one could think, virus spread, typhoon creation and floods give a sample that speaks for itself).
Wireless sensor devices turn out to have a well-suited potential for many application areas in less developed countries. Because of their self-organising characteristics and robustness, wireless sensor networks can be deployed in less benign environments and inaccessible places as well as in places where employing humans is difficult or costly. Although back-end communication infrastructures are needed to interface wireless sensor networks with the Internet or a local area network, they can also function in the absence of any communication infrastructures. This makes them particularly attractive for developing countries where the presence of stable communication infrastructures as a prerequisite for deploying computing systems may not be feasible. Today, a wireless sensor network is almost the only ICT means we have that can operate independent of any external communication infrastructure or/and electricity network. The CLAP validation results show promising potential in this area.
CLAP has been implemented in line with scientific and technical objectives of the project plan and all work packages have obtained relevant outcomes. Some scientific proposals have arisen from the project work and will be further studied. The CLAP research work has been presented in international conferences.
Information about the project and post-project actions is available at: http://web. media. mit. edu/~pantelis/index. htm
Wireless systems could significantly contribute to the development of technologically lagging rural areas especially in the developing countries, in addition to the development of rich and developed areas. In recent years, various wireless technologies have shown promise for a number of public applications, including elevation of quality of life of rural and/or unprivileged population. Such technologies include, among others, wireless ad hoc networks, wireless sensor networks, ubiquitous monitoring, location and experts systems. These technologies offer emerging opportunities that could effectively be used for smartening the environment as well as for improving the socio-economic status of the rural areas in the developing countries.
The Cross Layer Algorithms for PHealth (CLAP) project took into account resent research results in WSN, communication and collaborative environments and resulted in the design of a working prototype, based on the OLPC concept, which measures quality of life parameters. The initial motivation for this project and the main aim for implementing it is to benefit from low-cost, low-power wireless technologies to facilitate bridging the ICT scientific advances and implementation gap in developing countries, by bringing rural areas closer to their government and governments of developing countries closer to the technological level of the developed world in an ICT4D (Information and Communication Technologies for Development) manner.
CLAP carried out a first classification of MAC protocols, cross-layer techniques, cooperative transmission and strategies from previous European projects, standardisation bodies and literature. In parallel, CLAP determined the features of the relevant standards and open literature proposals that must be taken into account in the development of simulators, algorithms and models. The team proceeded to the specification of the architecture and functionality of a WSN, suitable for including cross-layer and cooperative transmission concepts, whereas the services that could be demanded in the next years were defined and a set of QoS requirements was also established. Having identified the initial set of the CLAP cross-layer techniques and cooperative protocols, the proposed architectures and mechanisms were validated.
The conceptualised framework of CLAP consists of four interacting clouds. Wireless sensor networks collect data monitoring QoL parameters, like the environment (water, soil, air, volcano), vital signs, health related human receptors, behavioral patterns. This is referred as cloud A. In this cloud, sensors are deployed in crucial parts of the rural areas, that could range from river banks, geographically challenging parts (for example; hilly areas), schools, gathering places, homes, down to individuals. The sensor networks could collect various critical data (e. g., level of water in the rivers which could help for flood warning, earthquakes etc.) and send them to gateways (sinks is a term widely found in WSN literature as well) referred as cloud B. In our framework a cloud B is implemented by networked communities that pre-exist for some other reason or are formed for this particular case. Examples of such network communities may be found in a OLPC equipped village, a mobile phones carrying community or a hospital on wheels, a vehicle mounted medical facility with wireless access functionality. A cloud B may move around the rural areas and serve many clouds A implementations or may be attached to only one and collect data only from them.
Data communication from a cloud B to the outer world is performed by facilities referred as cloud C. The major task of a cloud C implementation is to ensure reliable acquisition and delivery of data from the rural areas to a centrally located center referred as cloud D. A cloud C facility is capable of (wirelessly) communicating data acting as a repeater or router. It may additionally have capabilities for incoming data to be stored temporarily and/or processed. Examples of cloud C implementations may range from very simple solutions of one single PDA carried by a mailman or a drinking water distributor, to more complex facilities of satellite-linked equipment or vehicle mounted communication amenities.
A cloud D collects (processed or raw) data from cloud B installations communicated through the corresponding cloud C facilities. A cloud D would combine this data with data from other cloud A data and past records for a particular rural area or a number of selected areas and supply it to a referral center (which could also combine decision and action government powers). In this way, the government gets the timely and processed data from the rural areas and decides on the necessary actions accordingly. This data not only helps the government provide various services to rural areas and make educative strategic decisions and planning (as for example by monitoring behavioural patterns and socio-economic indicators), but could also help in emergency situations as well as for prevention (among the many examples one could think, virus spread, typhoon creation and floods give a sample that speaks for itself).
Wireless sensor devices turn out to have a well-suited potential for many application areas in less developed countries. Because of their self-organising characteristics and robustness, wireless sensor networks can be deployed in less benign environments and inaccessible places as well as in places where employing humans is difficult or costly. Although back-end communication infrastructures are needed to interface wireless sensor networks with the Internet or a local area network, they can also function in the absence of any communication infrastructures. This makes them particularly attractive for developing countries where the presence of stable communication infrastructures as a prerequisite for deploying computing systems may not be feasible. Today, a wireless sensor network is almost the only ICT means we have that can operate independent of any external communication infrastructure or/and electricity network. The CLAP validation results show promising potential in this area.
CLAP has been implemented in line with scientific and technical objectives of the project plan and all work packages have obtained relevant outcomes. Some scientific proposals have arisen from the project work and will be further studied. The CLAP research work has been presented in international conferences.
Information about the project and post-project actions is available at: http://web. media. mit. edu/~pantelis/index. htm