The  compression load cell is that the benefits of  organic sensors are much less impressive today than they were in 2013. The promises of excellent low-light performance and significantly better dynamic range will have to be compared to sensor technology. today's technologies rather than more existing technologies. more than a decade ago.
The principle of Treetscope is very simple, until now still limited to the field of R&D but never put into practice: measure the vital water consumption of trees from the inside and reevaluate irrigation measures based on on this data.
 
 This startup has developed a sensor  placed directly into the stem or trunk  of a tree, which uses temperature increases  to monitor the plant's water absorption – based on the principle that this action consumes water. consumes energy, thereby generating heat.
 
 The data collected by the sensor is transmitted to an analytical algorithm, which translates  changes in temperature into the amount of water absorbed by the installation.
 

 
 At this point,  probably don't expect to see a camera using Panasoic's now legendary organic sensor. I love Panasonic cameras and have used them extensively in my professional work for many years. The majority of PetaPixel's YouTube videos are shot with Panasonic cameras.They are amazing and we don't need  organic sensors to be a huge success for the company to keep winning. There's nothing wrong with leaving this ten-year experience behind.
 
 Last year I mocked this shear beam load cell by implying that it was almost stuck in the Phantom Zone, and this year I haven't seen anything  that would change my opinion.
 “If we make a new camera, we might choose this type of sensor,” Nakanishi said, referring to  organic sensors. “But it's an R&D job. So it's not [sure] whether we will use this sensor for the next camera or not."
 
 He said that while the company is  open to new technologies in the development phase, it has to weigh the pros and cons of what it chooses, and so far, organic sensors have not been choose  based on this analysis.
 
 It's unlikely that many are  still holding out hope that Panasonic's organic image sensors will  find their way into  new cameras, as many signs in recent years have "makes people doubt the viability of the sensor. I still don't know when it will be implemented because we already have customers but the developer wants to bring it to market in a few years", representative the company  said last year. In the future, organic sensors seem unlikely to be commercially viable, and Panasonic's language seems to be the same. indicates that internally the company is choosing not to select  organic sensors for its own projects.According to this logic, why would anyone else do it?
 
 As mentioned last year, Sigma gets the most  attention when it comes to sensors that are stuck in development, but at least the company's CEO Kazuto Yamaki has been open and frank about  progress of the full-frame Foveon sensor.
 

 
 From creating images, creating miniature torque sensor, and enabling self-driving cars, the application potential  of artificial intelligence (AI) technology is vast and transformative. However, all of these capabilities come at a very high energy cost.For example, estimates indicate that  OPEN AI's popular GPT-3 model consumed more than 1,287 MWh, enough to power the average US household for 120 years. This energy cost poses a significant barrier, especially to the use of AI in large-scale applications such as health monitoring, where large amounts of important health information are sent to centers. Centralized data  for processing. Not only does this consume a lot of power, but it also raises concerns about durability, bandwidth costs, and
 communication latency.Implementing AI-based health monitoring and biodiagnostics requires a standalone sensor that operates independently without a constant connection to a central server.

https://www.bransloadcell.com/html/en/torquesensor/