EXPERIMENTAL SETUP FOR SENSOR-BASED MONITORING OF ENVIRONMENTAL CONDITIONS

  • I. N. Oteyo School of Computing and IT, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
  • S. Kimani Software Languages Lab, Vrije Universiteit Brussel, Brussels, Belgium
Keywords: cloud computing, IoT, plant breeding, weather information

Abstract

The evolution of smart sensors has made data capture and relaying a lot easier. Smart sensors can be used to capture real-time data that can be used to improve the decision-making process. The sensors can help in monitoring environmental conditions in different use case scenarios. In agricultural research, this information is essential in determining different actions that can be taken in the research value chain e.g., when to water the plants under investigation if certain conditions are surpassed. Good environmental conditions have a direct influence on the success of the research experiments. These conditions can be monitored using different approaches. In this paper, we describe a sensor-based approach for monitoring these conditions. In the approach, we deploy sensors to monitor environmental conditions in the trial fields for plant breeding research. The data is collected using smart sensors and relayed to servers for processing and storage. The processed data is presented to the end users in form of visual graphs which can be viewed using mobile and web interfaces. The visual representations give the end users some insights on better interpretation and understanding of the data collected and help them make better decisions on the kind of actions to take. By deploying sensors to monitor environmental conditions, we seek to understand how the depThe evolution of smart sensors has made data capture and relaying a lot easier. Smart sensors can be used to capture real-time data that can be used to improve the decision-making process. The sensors can help in monitoring environmental conditions in different use case scenarios. In agricultural research, this information is essential in determining different actions that can be taken in the research value chain e.g., when to water the plants under investigation if certain conditions are surpassed. Good environmental conditions have a direct influence on the success of the research experiments. These conditions can be monitored using different approaches. In this paper, we describe a sensor-based approach for monitoring these conditions. In the approach, we deploy sensors to monitor environmental conditions in the trial fields for plant breeding research. The data is collected using smart sensors and relayed to servers for processing and storage. The processed data is presented to the end users in form of visual graphs which can be viewed using mobile and web interfaces. The visual representations give the end users some insights on better interpretation and understanding of the data collected and help them make better decisions on the kind of actions to take. By deploying sensors to monitor environmental conditions, we seek to understand how the deployment can be done in resource-constrained environments and the challenges that are likely to arise. We also aim to help researchers successfully execute field trials for target crops under plant breeding studies. Our main contributions are twofold. First, we present our experiences which can help in informing future studies. And second, we describe the challenges faced in deploying the sensor-based infrastructure in resource-constrained environments that are common in developing countries. In our preliminary findings we observe that among other challenges in developing countries, field trials for plant breeding studies happen in remote areas that are far from basic amenities like access to electricity and internet connectivity. For sensor-based infrastructure, these two resources are fundamental. This presents inherent research opportunities to be addressed and provide alternatives to the raised challenges. Future work entails investigating the sensor positioning (strategies) for seamless and optimal data collection experience.loyment can be done in resource-constrained environments and the challenges that are likely to arise. We also aim to help researchers successfully execute field trials for target crops under plant breeding studies. Our main contributions are twofold. First, we present our experiences which can help in informing future studies. And second, we describe the challenges faced in deploying the sensor-based infrastructure in resource-constrained environments that are common in developing countries. In our preliminary findings we observe that among other challenges in developing countries, field trials for plant breeding studies happen in remote areas that are far from basic amenities like access to electricity and internet connectivity. For sensor-based infrastructure, these two resources are fundamental. This presents inherent research opportunities to be addressed and provide alternatives to the raised challenges. Future work entails investigating the sensor positioning (strategies) for seamless and optimal data collection experience.

Published
2019-07-15