When deciding on using wireless systems to Sri Lanka various matters have to be looked into before coming to the final conclusion of it. For example a typical sensor board used for these applications costs around two hundred dollars and the sensors it self has prices ranging form fifty dollars onwards. Even though companies say that this is an affordable solution as for a third world country like us this may not be a very cheap solution. If we were to develop a sensor based system for farmers in our country the costs we incur will be great and sometimes may not be feasible when compared to the available solutions. Furthermore in countries like ours the where labor cost is very low a farmer can afford about ten laborers at the cost of a single sensor. So converting form this manual labor system to a high technological solution like sensor networks in our country may not be easy.
In Virginia vineyard deployments the elevation of the vineyard can be used to plant different types of vines using it in collaboration with temperature data so this situation can be applied directly to our paddy fields. Paddy is cultivated in our country in different elevations at different time throughout the year so by using sensor networks we can measure temperature and other factors that affect quality of the paddy and the feed the data in to appropriate agricultural model to find out which paddy should be cultivated were and in what condition does it give us the maximum yield. This system can be equally applied to other agricultural locations such as vegetable fields.
In Sri Lanka most farmers use fertilizers to get the maximum out of their crop and especially nitrogen based fertilizers. Nitrogen helps a plant to grow but according certain researches carried out more nitrogen can reduce the quality of the crop because of a phenomenon called the nitrogen stress. There are optical sensors created to measure the amount of nitrogen incident on a plant by using the reflective spectrum of the leaves of the plant. But the problem is there are no commercially available wireless optical sensors hence the sensing of nitrogen or other phenomenon using optical sensors should be carried out manually through out the field. But this is a good solution if we can tell our farmers when fertilizers are really required rather than applying fertilizers by consensus. This system can be extended to check the water purity before applying it to the crop and recommendations to clean the water if found not up to standard.
Water quality checks can also be applied to the public water systems as well. When considering the above given deployments the Lofar Agro project is in a much more applicable domain to Sri Lanka than the vineyards. Even the Indian sensor network deployment is more practically applicable to us but the projects itself lacks the maturity. When coming to water-management we can use soil moisture probes on the dry zone fields of Sri Lanka and especially in the semi-arid regions where the farmers cultivate using rain water and where very little irrigation is present. It is very feasible system if we could predict the areas of the field that watering is required. This can in turn be beneficial to a country like us because we can then take the maximum out of our water resource. When considering the architecture of networks to be deployed in Sri Lanka it is much better to have a self organizing network compared to data mule systems and table driven protocols. Even tough this is an expensive solution this is a feasible solution in the long term. Because when sensor systems are deployed in our country there is tendency of sensors getting lost or damaged and expansion of fields with time points more towards an ad-hoc network. If we use a table based system we could easily run into trouble with lost nodes.Our country has a large labor pool to draw from and in agriculture there is constant movement through the fields. But the data mule system is not an option because the cost of deploying the sensor network and then also using people as mules is a much larger cost to incur hence this system is infeasible.
In Virginia vineyard deployments the elevation of the vineyard can be used to plant different types of vines using it in collaboration with temperature data so this situation can be applied directly to our paddy fields. Paddy is cultivated in our country in different elevations at different time throughout the year so by using sensor networks we can measure temperature and other factors that affect quality of the paddy and the feed the data in to appropriate agricultural model to find out which paddy should be cultivated were and in what condition does it give us the maximum yield. This system can be equally applied to other agricultural locations such as vegetable fields.
In Sri Lanka most farmers use fertilizers to get the maximum out of their crop and especially nitrogen based fertilizers. Nitrogen helps a plant to grow but according certain researches carried out more nitrogen can reduce the quality of the crop because of a phenomenon called the nitrogen stress. There are optical sensors created to measure the amount of nitrogen incident on a plant by using the reflective spectrum of the leaves of the plant. But the problem is there are no commercially available wireless optical sensors hence the sensing of nitrogen or other phenomenon using optical sensors should be carried out manually through out the field. But this is a good solution if we can tell our farmers when fertilizers are really required rather than applying fertilizers by consensus. This system can be extended to check the water purity before applying it to the crop and recommendations to clean the water if found not up to standard.
Water quality checks can also be applied to the public water systems as well. When considering the above given deployments the Lofar Agro project is in a much more applicable domain to Sri Lanka than the vineyards. Even the Indian sensor network deployment is more practically applicable to us but the projects itself lacks the maturity. When coming to water-management we can use soil moisture probes on the dry zone fields of Sri Lanka and especially in the semi-arid regions where the farmers cultivate using rain water and where very little irrigation is present. It is very feasible system if we could predict the areas of the field that watering is required. This can in turn be beneficial to a country like us because we can then take the maximum out of our water resource. When considering the architecture of networks to be deployed in Sri Lanka it is much better to have a self organizing network compared to data mule systems and table driven protocols. Even tough this is an expensive solution this is a feasible solution in the long term. Because when sensor systems are deployed in our country there is tendency of sensors getting lost or damaged and expansion of fields with time points more towards an ad-hoc network. If we use a table based system we could easily run into trouble with lost nodes.Our country has a large labor pool to draw from and in agriculture there is constant movement through the fields. But the data mule system is not an option because the cost of deploying the sensor network and then also using people as mules is a much larger cost to incur hence this system is infeasible.
