Lessons from the Sparse Sensor Network Deployment in Rural India

We discuss the key issues in the deployment of sparse sensor networks. The network monitors several environment parameters and is deployed in a semi-arid region for the benefit of small and marginal farmers. We begin by discussing the problems of an existing unreliable 1 sq km sparse network deployed in a village. The proposed solutions are implemented in a new cluster. The new cluster is a reliable 5 sq km network. Our contributions are two fold. Firstly, we describe a. novel methodology to deploy a sparse reliable data gathering sensor network and evaluate the ``safe distance'' or ``reliable'' distance between nodes using propagation models. Secondly, we address the problem of transporting data from rural aggregation servers to urban data centres. This paper tracks our steps in deploying a sensor network in a village,in India, trying to provide better diagnosis for better crop management. Keywords - Rural, Agriculture, CTRS, Sparse.

Farmers' vulnerability to climate variability in Dimapur district of Nagaland, India

Certain parts of the State of Nagaland situated in the northeastern region of India have been experiencing rainfall deficit over the past few years leading to severe drought-like conditions, which is likely to be aggravated under a climate change scenario. The state has already incurred considerable losses in the agricultural sector. Regional vulnerability assessments need to be carried out in order to help policy makers and planners formulate and implement effective drought management strategies. The present study uses an 'index-based approach' to quantify the climate variability-induced vulnerability of farmers in five villages of Dimapur district, Nagaland. Indicators, which are reflective of the exposure, sensitivity and adaptive capacity of the farmers to drought, were quantified on the basis of primary data generated through household surveys and participatory rural appraisal supplemented by secondary data in order to calculate a composite vulnerability index. The composite vulnerability index of village New Showba was found to be the least, while Zutovi, the highest. The overall results reveal that biophysical characteristics contribute the most to overall vulnerability. Some potential adaptation strategies were also identified based on observations and discussions with the villagers.

Design of a TDD Multisector TDM MAC for the WiFiRe Proposal for Rural Broadband Access

The WiFiRe (WiFi Rural Extension) proposal for rural broadband access is being developed under the aegis of CEWIT. The system leverages the widely available, and highly cost-reduced, WiFi chipsets. However, only the physical layer from these chipsets is retained. A single base station carries several WiFi transceivers, each serving one sector of the cell, and all operating on the same WiFi channel in a time division duplex (TDD) manner. We replace the contention based WiFi MAC with a single-channel TDD multisector TDM MAC similar to the WiMax MAC. In this paper we discuss in detail the issues in designing such a MAC for the purpose of carrying packet voice telephony and for Internet access. The problem of determining the optimal spatial reuse is formulated and the optimal spatial reuse and the corresponding cell size is derived. Then the voice and data scheduler is designed. It is shown how throughput fairness can be implemented in the data scheduler. A capacity assessment of the system is also provided.

Rural energy consumption patterns - A field study

This paper is a condensed version of the final report of a detailed field study of rural energy consumption patterns in six villages located west of Bangalore in the dry belt of Karnataka State in India. The study was carried out in two phases; first, a pilot study of four villages and second, the detailed study of six villages, the populations of which varied from around 350 to about 950. The pilot survey ended in late 1976, and most of the data was collected for the main project in 1977. Processing of the collected data was completed in 1980. The aim was to carry out a census survey, rather than a sample study. Hence, considerable effort was expended in production of both a suitable questionnaire, ensuring that all respondents were contacted, and devising methods which would accurately reflect the actual energy use in various energy-utilising activities. In the end, 560 households out of 578 (97%) were surveyed. The following ranking was found for the various energy sources in order of average percentage contribution to the annual total energy requirement: firewood, 81·6%; human energy, 7·7%; animal energy, 2·7%; kerosene, 2·1%; electricity, 0·6% and all other sources (rice husks, agro-wastes, coal and diesel fuel), 5·3%. In other words commercial fuels made only a small contribution to the overall energy use. It should be noted that dung cakes are not burned in this region. The average energy use pattern, sector by sector, again on a percentage basis, was as follows: domestic, 88·3%; industry, 4·7%; agriculture, 4·3%; lighting, 2·2% and transport, 0·5%. The total annual per capita energy consumption was 12·6 ± 1·2 GJ, giving an average annual household consumption of around 78·6 GJ.

Energy and rural buildings in India

This paper attempts to evaluate the energy inputs needed to produce rural buildings. Based on a survey, a comparison is carried out of traditional and innovative technologies with reference to their energy consumption. Some basic data regarding energies in transportation are also presented. The implications of this analysis for development objectives is discussed.

Rural energy consumption patterns - A field study

This paper is a condensed version of the final report of a detailed field study of rural energy consumption patterns in six villages located west of Bangalore in the dry belt of Karnataka State in India. The study was carried out in two phases; first, a pilot study of four villages and second, the detailed study of six villages, the populations of which varied from around 350 to about 950. The pilot survey ended in late 1976, and most of the data was collected for the main project in 1977. Processing of the collected data was completed in 1980. The aim was to carry out a census survey, rather than a sample study. Hence, considerable effort was expended in production of both a suitable questionnaire, ensuring that all respondents were contacted, and devising methods which would accurately reflect the actual energy use in various energy-utilising activities. In the end, 560 households out of 578 (97%) were surveyed. The following ranking was found for the various energy sources in order of average percentage contribution to the annual total energy requirement: firewood, 81A·6%; human energy, 7A·7%; animal energy, 2A·7%; kerosene, 2A·1%; electricity, 0A·6% and all other sources (rice husks, agro-wastes, coal and diesel fuel), 5A·3%. In other words commercial fuels made only a small contribution to the overall energy use. It should be noted that dung cakes are not burned in this region. The average energy use pattern, sector by sector, again on a percentage basis, was as follows: domestic, 88A·3%; industry, 4A·7%; agriculture, 4A·3%; lighting, 2A·2% and transport, 0A·5%. The total annual per capita energy consumption was 12A·6 A± 1A·2 GJ, giving an average annual household consumption of around 78A·6 GJ.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

Predictive testing for familial adenomatous polyposis in a rural South Indian community

During the course of genome studies in a rural community in the South Indian state of Karnataka, DNA-based investigations and counselling for familial adenomatous polyposis (FAP) were requested via the community physician. The proposita died in 1940 and FAP had been clinically diagnosed in 2 of her 5 children, both deceased. DNA samples from 2 affected individuals in the third generation were screened for mutations in the APC gene, and a frame-shift mutation was identified in exon 15 with a common deletion at codon 1061. Predictive testing for the mutation was then organized on a voluntary basis. There were 11 positive tests, including confirmatory positives on 2 persons diagnosed by colonoscopy, and to date surgery has been successfully undertaken on 3 previously undiagnosed adults. The ongoing success of the study indicates that, with appropriate access to the facilities offered by collaborating centres, predictive testing is feasible for diseases such as FAP and could be of significant benefit to communities in economically less developed countries.

Sustainable bioenergy production strategies for rural India

The paper aims to assess the potential of decentralized bioenergy technologies in meeting rural energy needs and reducing carbon dioxide (CO2) emissions. Decentralized energy planning is carried out for the year 2005 and 2020. Decentralized energy planning model using goal programming technique is applied for different decentralized scales (village to a district) for obtaining the optimal mix of energy resources and technologies. Results show that it is possible to meet the energy requirements of all the services that are necessary to promote development and improve the quality of life in rural areas from village to district scale, by utilizing the locally available energy resources such as cattle dung, leaf litter and woody biomass feedstock from bioenergy plantation on wastelands. The decentralized energy planning model shows that biomass feedstock required at village to district level can even be obtained from biomass conserved by shifting to biogas for cooking. Under sustainable development scenario, the decentralized energy planning model shows that there is negligible emission of CO2, oxide of Sulphur (SOx) and oxide of nitrogen (NOx), even while meeting all the energy needs.

A systems approach to rural housing

An attempt is made in this paper to arrive at a methodology for generating building technologies appropriate to rural housing. An evaluation of traditional modern' technologies currently in use reveals the need for alternatives. The lacunae in the presently available technologies also lead to a definition of rural housing needs. It is emphasised that contending technologies must establish a 'goodness of fit' between the house form and the pattern of needs. A systems viewpoint which looks at the dynamic process of building construction and the static structure of the building is then suggested as a means to match the technologies to the needs. The process viewpoint emphasises the role of building materials production and transportation in achieving desired building performances. A couple of examples of technological alternatives like the compacted soil block and the polythene-stabilised soil roof covering are then discussed. The static structural system viewpoint is then studied to arrive at methodologies of cost reduction. An illustrative analysis is carried out using the dynamic programming technique, to arrive at combinations of alternatives for the building components which lead to cost reduction. Some of the technological options are then evaluated against the need patterns. Finally, a guideline for developments in building technology is suggested

Forecasting rain for groundnut farmers�how good is good enough

: We illustrate how climatological information about adverse weather events and meteorological forecasts (when available) can be used to decide between alternative strategies so as to maximize the long-term average returns for rainfed groundnut in semi-arid parts of Karnataka, We show that until the skill of the forecast, i.e. probability of an adverse event occurring when it is forecast, is above a certain threshold, the forecast has no impact on the optimum strategy, This threshold is determined by the loss in yield due to the adverse weather event and the cost of the mitigatory measures, For the specific case of groundnut, it is found that while for combating some pests/diseases, climatological information is adequate, for others a forecast of sufficient skill would have a significant impact on the productivity.

Counselling and predictive testing for familial adenomatous polyposis in a rural South Indian community

Background—Mutations of the APC gene cause familial adenomatous polyposis (FAP), a hereditary colorectal cancer predisposition syndrome.Aims—To conduct a cost comparison analysis of predictive genetic testing versus conventional clinical screening for individuals at risk of inheriting FAP, using the perspective of a third party payer. Methods—All direct health care costs for both screening strategies were measured according to time and motion, and the expected costs evaluated using a decision analysis model.Results—The baseline analysis predicted that screening a prototype FAP family would cost $4975/£3109 by molecular testingand $8031/£5019 by clinical screening strategy, when family members were monitored with the same frequency of clinical surveillance (every two to three years). Sensitivity analyses revealed that the genetic testing approach is cost saving for key variables including the kindred size, the age of screening onset, and the cost of mutation identification in a proband. However, if the APC mutation carriers were monitored at an increased (annual) frequency, the cost of the genetic screening strategy increased to $7483/ £4677 and was especially sensitive to variability in age of onset of screening, family size, and cost of genetic testing of at risk relatives. Conclusions—In FAP kindreds, a predictive genetic testing strategy costs less than conventional clinical screening, provided that the frequency of surveillance is identical using either strategy. An additional significant benefit is the elimination of unnecessary colonic examinations for those family members found to be noncarriers.