arnowa’s forest monitoring system uses a variety of smart sensors and camera to monitor environmental parameter, fire presence, pest infestation, animal movement and soil health.  the sensor output is tirelessly interrogated and modelled by cutting-edge data, image and video analytics.  artificial intelligence (ai) and machine learning (ml) continually optimise these models, facilitating the immediate detection of detrimental events such as forest fires and illegal logging. real-time alerts are delivered to authorities, enabling rapid response and minimising the risk of forest destruction. it can be used in known fire risk localities, areas suspected of illegal logging activity, national parks, forests and animal corridors.

our wetland management solution ~ “jeewan” consists of multi-parameter sensors for water quality (such as ph, turbidity, tds, etc.), connected to the wireless data transfer protocol through the arnowa nodes. our edge and cloud computing then processes this data and builds models based on big-data analytics, ai, and machine learning to predict the future trend of the water quality, helping prepare stakeholders for suitable action and empower decision making so that water pollution can be prevented.

arnowa’s forest monitoring system uses a variety of smart sensors and camera to monitor environmental parameter, fire presence, pest infestation, animal movement and soil health.  the sensor output is tirelessly interrogated and modelled by cutting-edge data, image and video analytics.  artificial intelligence (ai) and machine learning (ml) continually optimise these models, facilitating the immediate detection of detrimental events such as forest fires and illegal logging. real-time alerts are delivered to authorities, enabling rapid response and minimising the risk of forest destruction. it can be used in known fire risk localities, areas suspected of illegal logging activity, national parks, forests and animal corridors.

our wetland management solution ~ “jeewan” consists of multi-parameter sensors for water quality (such as ph, turbidity, tds, etc.), connected to the wireless data transfer protocol through the arnowa nodes. our edge and cloud computing then processes this data and builds models based on big-data analytics, ai, and machine learning to predict the future trend of the water quality, helping prepare stakeholders for suitable action and empower decision making so that water pollution can be prevented.