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We’re entering a new era of intelligent man-made devices communicating with each other and exchanging data. Machine-to-machine communications is now being called "the Internet of Things" and this will transform the way much business is conducted.

When a device such as a sensor or a meter registers an event such as a temperature measurement, a salinity reading exceeding a specified threshold value, or a retail item being purchased, the event data is sent via a network to software programs that can store and transform the data which typically includes the location of each event. Appropriately geo-enabled Business Intelligence tools can then be applied to help make sense of the data within the context of the location relationships between data sources. As with everything to do with Internet, the amount of data will grow with the variety of sources, aggravating that perennial conundrum of understanding of the accuracy and quality of the data. One assumption is that the extra network traffic caused by high level communication protocols and verbose content encoding will be a minor issue as broadband communications becomes more widespread.

What is new today is the plug-n-play Internet connectivity of devices and their availability. Unsurprisingly there’s still a long way to go before the proprietary data and control interfaces built for their specific software and hardware systems move to new open industry standards to enable an effective and useful mass exchange of data.

For several decades telecommunications has been in the vanguard of this movement as progressively more intelligent devices got pushed to the edges of their networks. Managing such devices, controlling the flow of data between them and most importantly managing the layer of services utilising that data is something our development team at Integeo has been deeply involved with since the early 1990s. Many of the associated problems we addressed when developing distributed telecommunications management systems are only now starting to be recognised and understood by the IoT propagandinistas.

An Early Forge Example of IoT In Action

article IoT 01An illustrative example of our work is a supply chain system that our company built and deployed over ten years ago. Around the world hundreds of thousands of refrigerated containers are used to transport foodstuff, vaccines and other temperature sensitive products around the globe. The monitoring of a container's environment traditionally involves simple recording devices which results in the spoilage of goods only being discovered when the containers are opened at their destination, which can affect as many as 7% of shipments. This spoilage in transit is often because of such preventable causes as a refrigeration unit icing up or the power being turned off.

We developed a system that managed sensors attached to the container and its contents. The sensors sent real-time alarms based on customer-defined conditions such as doors being opened, temperatures exceeding pre-determined limits, or power outages. Subject to a valid service subscription, exporters and shippers could view the current and historical data of their container or goods over the Internet, or they could choose to only look at shipments when they received an email or SMS alarm. The system managed all the remote devices, the collected data, the subscriptions and the transmission of alarms and data to customers.

The sensors enabled customers to check on the condition of sensitive, in transit cargo via a secure web-site, ie: from when the cargo is first packed, in terminal, to being at sea through to arrival at consignee. Information was securely transmitted via a number of communication channels to the management system, which then distributed customer updates via e-mail, WAP3 or SMS. The system managed customer service subscriptions which involved setting associated alarm thresholds and notification preferences.


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The success of all businesses and organisations depends on accurate identification of needs, and the effective delivery of solutions to those needs. Delivery requires timely access to related data and the ability to understand the information implicit in the data. From this basis you can advance group knowledge via analytics and so become better positioned to make informed decisions.

Business Intelligence is a process of translating information into insights, enabling people to dynamically create and interact with data, exploring and seeing the data represented in a variety of complementary visualisations.

Location transcends landscape, climate, and buildings. Data has more meaning when placed its real-world context but constructing the location context of data is a lot more than latitude and longitude coordinates.

So what is location context and how do you put it to use?



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We’re entering a new era of intelligent man-made devices communicating with each other and exchanging data. Machine-to-machine communications is now being called "the Internet of Things" and this will transform the way much business is conducted.

In spite of all the hype the IoT is definitely not just smoke and mirrors. Howard Dresner, founder and chief research officer at Dresner Advisory Services predicts that as the IoT stack matures with more businesses building IoT systems, then location intelligence will rise in importance across all industries because first and foremost the IoT is about where stuff is.

Forge has been working in the field of distributed computing for over twenty years. An illustrative example of our work is a supply chain system that our company built over ten years ago.



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Our experience and skills are increasingly relevant as intelligence and decisioning power moves to the edges of networks, with the rise of automated decision making systems and as companies involved with remote sensing move from just delivering imagery towards delivering alerts when something changes. We have deep development experience with:

  • the merging worlds of Business Intelligence and Location Intelligence
  • the application of evolving, complex standards (open and proprietary) - e.g. standards being developed under the auspices of the Open Interconnect Consortium and the OGC OM Sensor Web
  • highly complex systems requirements
  • cooperation with external teams – especially with hardware/firmware vendors
  • large scale software development involving large teams over many years


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