The world population is continuously increasing and is predicted to reach 9 billion people in 2015. It causes a lot of problem including water availability and food security. Globally, there are 2 billion people living in the risk of reduced access to freshwater. Meanwhile, the Indonesian Ministry of Agriculture reported that 80% of the available water in Indonesia is utilized for agricultural activity. It surely makes the agriculture in Indonesia is not yet sustainable. Another serious problem is there are 815 million people globally are undernourished and it is predicted that there will be the addition of 2 billion people in 2050 (United Nations). The Global Hunger Index reported that Indonesia is categorized as a nation with a serious food security problem. On the other hand, there is a substantial decrease of total number of farmers in Indonesia. Additionally, more than 60% of the farmers aged over 45 years old. Unfortunately, the human dependency in the agricultural sector in Indonesia is very high. These facts would indeed cause a dangerous problem for us if there is no change in the agriculture operational system.
We develop ENCOMOTION, a machine-to-machine IoT technology that enables farmers to irrigate the farm precisely and automatically. It records the environmental data and with the cloud computing method they are processed with the result of the crops water need. Then, the data is sent to the controlling system that is connected to the irrigation infrastructure. By having this integrated system, the farm is irrigated precisely and automatically. From the initial portfolio, we can show that applying ENCOMOTION can reduce the use of water by 40% while the productivity increased by 50%. In addition, our users are happy as they can focus on other farming activities instead of wasting time irrigating the farm. The latest fact shows that while it increases the farm productivity and sustainability, the human dependency in agriculture is decreasing.
There are similar other solutions in the market already utilizing the concept of IoT such as agriculture monitoring system through mobile application. Most of of them require the decision making process to be made by the farmers. Unfortunately, most of the farmers are not yet able to utilize the raw data to help them with the decision making process for the farm operation. Therefore, the smart algorithm embedded to the ENCOMOTION system would tackle that problem.
Comments