T42 Iot Tracking Solutions Share Discussion Threads

[dancing piranha] 17/5/2022 07:07

What about DHL?

[smithie6] 13/5/2022 12:58

Thanks

Share price been on a downward trend since 25-27p spike.

The rampers on the main msg board haven't been able to stop the share price falling.

[dancing piranha] 13/5/2022 08:36

I agree, I feel there is a cash raise coming.

[smithie6] 12/5/2022 17:43

Top stuff Smithie6

[dancing piranha] 12/5/2022 16:43

Bapodra,

Why do you think TRAC have appointed a new financial advisor?

[dancing piranha] 11/5/2022 15:09

Yawn....

Are DHL indecisive, undecided, or gone elsewhere? One has to wonder..... The silence is deafening!

[turbotrader2] 04/5/2022 20:38

And?The point????

[turbotrader2] 04/5/2022 20:37

I'm happy to hear

[glavey] 04/5/2022 06:30

"Positive news should see an upward directional move but not so positive could see it go downwards."

Inspired comment on the other thread. (For some unknown reason they don't want me to post anything over there, which probably serves as a confirmation of my view of TT)

[nig1954] 28/4/2022 09:34

Ports and their ability to operate as a transit hub – smoothly and efficiently – is under public scrutiny. Now it has become clear that congestion in ports is not only a concern for maritime and supply chain professionals but even for national economies. Ports have become the buffer zone struggling with peaks of the arrival of cargoes. This topic has become the subject of numerous discussions at the White House in light of the severe congestion at the West Coast ports. Simulations empowered by artificial intelligence (AI) systems can prove the point but even more so they can provide more insights which help to define the optimal opening hours per day based on predictions. This topic is central to discussions around the transformation towards smart ports which requires large-scale digitalization of businesses, governmental services, buildings, logistics and transport not at least infrastructure. The task is challenging as sea transport is managed with very limited predictability. Applying new approaches empowered by artificial intelligence (AI) can help to flatten the curve of truck arrivals at the port. The flows and their disruptions represent a major challenge for port authorities and also nearby cities. The port is the space where unsynchronized port-bound flows from the hinterland meet unsynchronized cargo flows arriving from the sea. The port is the buffer zone that has to absorb shocks caused from peaks at both ends. This logically requires flexibility through buffer zones or time reserves. In the US it is estimated that at least seven of the nation's 10 busiest ports by volume face congestion regularly. The situation has become a trade barrier with significant negative impact on national economies. The port, transport and logistics industry has basically two options to get back to normal. It could increase the pool of equipment to have spare capacity at its disposal so that when demand surges or supply is disrupted, the extra ships, containers, vehicles, and trailers can provide the additionally required supply. This is wasteful, costly, and inherently inefficient. Alternatively, it could introduce ways that allow the existing capacity to handle a larger volume of cargo. Real-life studies recently conducted demonstrate that AI systems can predict port container flows with high precision and furthermore that the prediction systems can calculate different scenarios as alternative ways of operating with different impacts on the fluidity of traffic flows informing about the benefits of different specific adjustments to the status quo. The modelling approach can be adapted to simulate effects of changes in operational parameters. Resource and traffic planner can utilize the traffic rate predictions to dynamically adjust resource allocations, e.g. to prepare in advance for days or weeks when peaks are predicted. The recommendation is thus not to expand opening hours per se but to adopt flexibility when peak times are predicted. The results of the real-life study in terms of predictability and simulation indicate the additional value that can be created through AI systems in a port environment through more regular utilization of road and port infrastructure by informing planners and decision-makers about alternative more favourable operating models. Their implementation would benefit the entire ecosystem and with that stakeholders and communities across the globe, like ports, cities, hinterland corridors, seaside carrier communities, and the global network of ports through higher fluidity of traffic flows which would improve financial results and reduce disruptions causing burdens and risks.
The adoption of such AI systems relies on the general understanding and conviction across major actors that optimizing cargo flows in the interconnected and interdependent self-organizing world of maritime supply chain networks requires a holistic view and approach with at least a minimum level of collaboration ensuring sufficient data sharing. Global maritime supply chains have been disrupted. Shipping companies wish to be quickly served, trucks and their drivers do not want to wait in line for hours to pick up a single container, train operators do not wish to leave ports with empty wagons, and ports do not want to have its infrastructure and resources on idle. AI systems enable the integration of different communities, like port, seaside and hinterland corridors which helps to deal with the disruptions through better and anticipative synchronization of cargo flows.
AI tools are immediately available and AI systems can quickly be built while expanding capacity takes time .With more optimized infrastructure utilization come many advantages and benefits, including cost and energy savings. AI powered predictions combined with slot management for visiting ships, trucks, and trains and their integration will provide the foundations for integrated and synchronized cargo flow management in the interest of the entire maritime supply chain network community. These real life studies are what national governments are currently considering. t42 is working in the right area and providing we can apply the most beneficial modelling from all of the data collected by our sensors then this will prove to be a very valuable asset which governments will wish to utilise for their own national interests. In a previous conversation with Igor he alluded to t42 having access to professional teams of modellers so I'm hoping this is something they've been working on behind the scenes. I've reason to believe that this is part of their new business strategy and they'll appreciate more than we do how valuable this asset will become as more data is collected and integrated with the modelling database.