UbiNET AI Blockchain

#UbiNET twin #AI #Blockchain with mutating #security #algorithm

UbiNET platform architecture is built on two key components;

  • a twin blockchain written in an AI codebase called UBI (originally based on Prolog with attributes of .NET) developed specifically for UbiNET
  • a mutating security algorithm derived from the unique platform functional architecture

By interlinking the security algorithm derived from every transaction only the next ordered AI Blockchain knows what the structure of an acceptable contract is.

is built on a that we own entirely . We have two that run the we own the too. We can any with

Phase 2 completed in 2016.

City

#Rural #UltraBroadband signals the end of a focus on #Cities instead #LiveSmart

One of the essential requirements for the IoT is integrated and distributed networks, until recently the only way possible to deliver this was either in cities with their high fidelity infrastructure or on a peer-to-peer mobile network using 4G. With the inception of recycled infrastructure by companies like Huawei and the deployment on 5G in 2020 cities cease to afford the benefits required to absorb the huge costs of their use.

The prediction of #Smart #Business is #Smarter not locating to a #SmartCity in 2016 by UbiNET CEO Karl Smith make the clear case of;

Why do we need cities?

They create centralization of people and resources however they also drive costs as often space is insufficient for demand. There is a huge dependency on the need for workspace, shops and local living accommodation.

Lets not buildSmart Cities, lets Live Smart instead

No City Smart Business

In a #SmartEconomy with people engaged in #SmartLiving people rely on digital communications not face to face engagements. Unless direct physical contact with another person is required for your job you don’t need to be physically present. Most work can be distributed to multiple locations across the planet. Even specialist surgeons can now work remotely and have been doing so for some time, even surgery can now be done through a physical / virtual interface.

Summary

The cost of creating Smart Cities is huge and relates to infrastructure for jobs and services that won’t be required in the mid term, they will not make a profit and may even not cover their cost of creation and installation.

The Smart solution is a distributed model not a centralized one

Creating these types of services takes a huge investment and without the confirmation of a captive customer base, it should be interesting to see how capital can be raised and who will take this risk.

Pi-UbiNET

UbiNET Inc. has incorporated as a subsidiary of Agile World

Last week Agile World created a new subsidiary UbiNET Inc. set up as a stock corporation to support several funding rounds to deliver it’s global technology, data and service platform. This change in strategy is due to an over subscription for Series A investment which has created a focus on investors outcomes.

The formation of UbiNET Inc. will have no immediate impact on staffing and facilities but it is intended to focus R&D on the open network ecosystem protocol already filed at USPO.

The CEO of Agile World Karl Smith described this change as “it’s fundamental that we have the business structures in place to enable investors to have clarity around their participation” further “having worked in global M&A and with VC funded start-up’s, I recognise that a good idea needs to be supported by and understanding of how to facilitate investment, engagement and exit”.

Further details will be published here.

UbiNET Inc.

#IoT3 #SmartTechnologies to #SmartLiving

Trajectory from Smart Technologies to IoT Ecosystem and on to Smart Living

Something few people have grasped yet is that to get from Smart Technologies to Smart Living (Ubiquity) is a progression, not just in sensors, networks and device thinking, but also in ecosystem and task (to discern if they are even relevant not just the form of them) thinking. As with every other revolution not only does time and people change the meaning of the revolution they also change the trajectory.

At the Global 5G Test Summit at MWC17 in Barcelona the panel was asked what services will 5G bring, extend or establish as the killer services, quite rightly the panel answered that the key services of 4G were not known until the network capability was in place and they evolved by adoption, not by strategy alone.

Three Stages of IoT Evolution

IoT Smart Technologies, #IoT1

Smart Technologies relates to limited networks of control actions, sensors and rules setting devices around a small number of tasks, specific locations or limited markets. They can be added to relatively easily but ultimately can’t manage a whole ecosystem, without replacement. An example would be managing home based utilities; there are already many systems that manage, heating, lighting and security in one system. These systems don’t manage the whole home and all the tasks in a home, so don’t manage the Home Ecosystem. They are also restricted to non complex tasks that that have binary or stepped rules for controlling tasks. For example setting the heating times, temperature, managing lighting, responding to a proximity alert for security, that can be locally or remotely set and observed.

IoT Closed Ecosystems, #IoT2

Closed Ecosystem IoT relates to a fully integrated system of several types of network including machine to machine M2M, machine to human M2H and machine to data system M2D through an application gateway. Additionally these networks provide pre-connected and situational relationships dependent upon tasks, locations and users. An example would be a Home Ecosystem, again as this is the most likely location to get investment at this point in human society.

All possible actions and interactions within a home, including disallow rules (security and safety), policies related to sensors and personal ecosystems are defined and can be added to by users with the correct rights (on matters of safety for example only Parents would have the rights to set safety rules). Every sensor device (item group made from many items with a micro sensor), task (with an outcome) and activity (outcome not essential), item (everything not an item group or a device) can be included in the ecosystem. Personal ecosystems (personal avatar plus id, agenda, voice print, payment), location ecosystems (kitchen, living room, garden etc.) and an Adoption / Attribution Ecosystem (to manage purchase, transit and adoption).

An example of a task would be, an item group close to arrival (washing machine), then arrives, the Home Ecosystem advises a Parent Ecosystem of arrival through audible or voice alert, the Parent working in the garden greets the delivery vocally while remaining in current location and opens the door. The delivery staff enter the property, confirm they are fitting the item group, when it is connected the House Ecosystem sends a request to the Parent Ecosystem, “diagnostics good, adopt?” the Parent says “Adopt”, the House add the item group to the Kitchen and Parent ecosystems and the House Ecosystem “Owned, Working, Value” and updates the Insurance provider, the fitters get a message Adopted and then leave. The Parent rates their service. While this is a simplified view and there are several other M2M processes that happen it shows that a closed Home Ecosystem enables the simplification of process and the ability for remote management of otherwise time consuming and stressful tasks.

IoT Smart Living, Open Ecosystems, UbiNET #IoT3

Open Ecosystem IoT is an evolution of IoT2 that enables an end to end lifecycle management of all items and item groups from material, through creation, use, disposal and recycling. It is not vested in Home only but also in Communities, States, Nations, Internationally and at Planet Level. It fundamentally changes our interactions, behaviors and relationship to work, institutions like banks and security.

#SmartLiving Payment Scenario – while having a coffee with a friend in their house a person sees a nice bowl and says, ‘buy bowl’. Their personal network checks the area and finds three bowls (items), it asks ‘white bowl’ the person says ‘Yes’ the bowl is ordered based upon the person’s personal preference which could be Speed, Price, Color or anything else, for this scenario it’s Speed the Protocol locates the nearest supplier and orders it for immediate delivery. The person carries on chatting and the bowel is delivered to their home and is waiting for when they get home. Payment is automated, they unpack look at the bowel and say, ‘Great Condition’ and feedback allocated is allocated to the carrier, the product and the supplier.

#SmartLiving Recycling Scenario – an item lifecycle is monitored from creation to recycling items that are not recycled retain a relationship with their last individual or other (structure like business or organisation) if should be but not recycled that relationship informs state and national law enforcement.

#SmartLiving Ownership Scenario – when an item is purchased it becomes added to several new ecosystems, individual, family, community, state and nation (if bought outside individual’s country of origin) advising national law enforcement of their status.

#SmartLiving Advance Security Scenario – items that are not recognized as being part of an ecosystem may not join one. Without full lifecycle data, the item will be considered to have no value, fraudulent or stolen. By using an inverse data analysis, a home or other place can detect a person that has no recognizable items and consider them a threat. They will not be allowed access and become the focus of Law Enforcement.

UbiNET Copyright © 2001 Agile World

UbiNET is the Agile World test platform also called Project Charlemagne using 5G and 6G concept where we are building scenarios for IoT3, linking blockchain, sensors and artificial intelligence, which forms the bases of the Open Network Ecosystem Protocol, patent.

Related Articles on Agile World

Situational awareness drives the IoT ecosystems and interactive landscape not visual interfaces

The foundation for this thinking goes back to a notion of the ‘social life of things’. If things themselves exist and have a number of trajectories and states then those things also potentially have accessible and useful human touch points in the IoT.

Much of the interactions we humans have become used to are in fact simple touch-points to hidden and complex interactions within dispersed and non-interlinked (at the core) technology systems. This simplification process of creating a directed visual presentation layer enables us to maintain a simplified mental model around our interactions. However in IoT technologies the additional integration of voice, touch and thought require a full understanding of the primary cognitive models for each IoT device and an associated and integrated cognitive model, possible clashes or drop outs and load descriptions (for each constantly changing eco-system) by Thing and Cognitive Group. Only then can an interface be defined.

situational networks with IoT devices services and humans

Above is a visual description of a set of Things available with a person walking through them projecting themselves, a simple human journey. However working in a local model gets the notion of Things and Cognitive Groups across. Each colour group represents a Thing, attempting to get our attention, each Thing does something different, a different set of interactions, activities, behaviours and outcomes. They can talk to each other or ignore each other. The person traversing the real world and IoT landscape walks through several fields of interaction, each time they enter a new field it communicates to them, availability, interaction, messaging (branding, cries for attention, warnings etc.). The first position P1 three touch-points seek engagement, by P2 it’s six touch-points, in P3 five touch-points seeking engagement.

There is no requirement for visual interfaces, in fact audio, smell or touch (vibration or texture) are more likely and in fact desirable to create the ambience for localised interaction and mental association.

Further the current cognitive models associated with the digital existence of tangibles may need to be reconsidered in the context of the IoT as it amalgamates previously separate constructs. It could simply be that the detailed component view we have constructed around daily interactions is no longer valid and we can simplify not only our interactive behaviour but also our descriptors by moving them to high level (directional and instructional avatar) understood constructs rather than the detailed process models we tend to use to live.