SENSORO - a worldwide leader in smart sensor and beacon technology - has chosen 
Graphcore systems to deliver the AI compute behind its latest environmental and 
safety monitoring systems.

Graphcore IPUs will power a range of SENSORO solutions, designed to help towns 
and cities become safer, greener places to live.

Smart sensors are emerging as an essential tool in the management of modern, 
urban environments as they transition to more sustainable forms of energy and 
transportation, while also dealing with the effects of climate change.

Fire, flood and fishing

SENSORO will initially use Graphcore IPU compute for:

Smart fire protection: The rapid growth in the use of electric bicycles has 
also seen an increase in e-bike charging fires. SENSORO's monitoring system can 
alert building managers to the arrival of an e-bike at their premises, allowing 
them to assist with safe charging procedure and facilities. 
Emergency flood prevention: Graphcore is working with SENSORO to develop early 
warning systems based on monitoring of urban flood risk areas, enabling better 
disaster preparedness and emergency response. 
Smart ecological governance: illegal river fishing breaks the ecological chain 
and destroys the integrity of the ecosystem. SENSORO systems are able to 
recognise different fishing scenarios, such as electric fishing and net 
fishing, providing accurate information on illegal fishing activity.
Computing foundation

SENSORO founder and CEO Tony Zhao welcomed our partnership, saying: 
"Graphcore's IPU system provides an efficient and easy-to-use computing 
platform for the urban ESG solution jointly created by both parties, and solves 
the computing power bottleneck that we have faced for a long time. We will be 
continuing to work with Graphcore, and using the IPU to deliver positive change 
in more aspects of people's lives."

YOLO

One of the main AI models used by SENSORO, running on Graphcore IPUs, is YOLO.

YOLO (You Only Look Once) is a highly effective convolutional neural network 
for real-time object detection. Since the release of the first version in 2015, 
it has undergone a number of refinements to improve speed and accuracy.

SENSORO found that the IPU's fine-grained and highly parallel compute 
capabilities lent themselves to the parallelisation required to get the most 
out of YOLO.

When running inference on high resolution images (1920x1080px), SENSORO saw a 
4X performance gain, compared to the GPU-based inference solution they had been 
using previously.

Source: Beijing SENSORO Technology Co. Ltd.

Image Attachments Links:

   Link: https://iop.asianetnews.net/view-attachment?attach-id=411586

   Caption: SENSORO smart city service system is applied in Yichang, Hubei 
Province

   Link: https://iop.asianetnews.net/view-attachment?attach-id=411588

   Caption: From left to right: Graphcore Mk2 IPU, Graphcore IPU-M2000