Agriculture is the backbone of our countries economy. It entails crop and livestock production. One of the major challenges in crop production is infection by diseases and pest infestation. Prevention and early control of crop infections and pest attack is key to boosting crop yield. However, there exist no technique for real time monitoring and detection of infections and infestations crops in the field.  As a result a farmer incurs huge cost in spraying crops to prevent possible diseases that might attack crops in the field – a process which is expensive and often not environmentally friendly. In case the crops are infected, the disease might take some time before it is visually noticed by a farmer. The intervention may be too late to save crop from massive loss of yield. Agricultural extension services are rare and sometimes not convenient as it takes time for experts to conduct extensive laboratory tests which are also expensive to a farmer. The ideal situation would be to have a technology for monitoring crops in the field as they grow. In case a disease or pests are detected, the farmer is immediately alerted so that urgent measures can be taken to prevent extensive crop damage.

A team of scientist from Meru University of Science and Technology has developed an electronic gadget for real time monitoring of crop diseases and pests in the field. The goal of the device is to alert a farmer during the onset of a crop disease or pest attack. The alert signal is in form of a sms message to his/her mobile phone describing the detected disease and the possible measure to be taken. The system comprises of camera modules interfaced to a miniaturized computer system. The system is programmed to capture images of the crops in the field periodically and process the images using advanced computer vision algorithms to determine the nature of the infection or infestation. A GSM module is attached to the system for communicating to the farmer when an anomaly is detected in the farm.  

The currently the system has be trained to diagnose bacteria wilt in tomatoes. The system has been thoroughly tested and impressive results regarding the device performance have been reported. We are now training the device to learn to diagnose other diseases and pests that affect a wide range of horticultural crops. The system can also be adopted to alert a farmer when crops are about to be ready for harvest and estimate the quantity of the harvest as while as serve as a CCTV Severance system in the farm.

Maiteithia with his student decoding information sent to their system