One of the main improvements in the IoT AggreGate Platform 5.5 release was machine learning, which gave data processing professionals a chance to extract required knowledge while analyzing time series streams and large data sets.
And more recently, we have added several algorithms allowing you to create trainable units with an option of online learning.
Such trainable units have two important features. The first is ability to train on a data set that is too large to fit into memory. The second is ability to update with new data that wasn’t available during initial learning.
In other words, a trainable unit can be trained on available data, used for predictions, and get updated as soon as new data arrives, which will improve the quality of further predictions.
Importantly, the trainable unit in this case is not trained from scratch, but updated, modifying its existing state with new training data set.
The plus point is that it takes significantly less time to complete online learning than would be needed for learning from scratch.
From this moment on, Tibbo Systems employs in-house corporate CRM system based on our AggreGate IoT Platform. At the system core, there is our new Classes module, i.e. relational or graph data storage access interface. We used Classes to model typical CRM objects (Accounts, Contacts, Leads, Opportunities, Agreements, etc.) and their relations.
In addition to default CRM features, the solution comes with document flow module (migrated from SharePoint). The shift to AggreGate CRM system allowed to reduce costs and integrate the solution with other corporate systems for full-fledged and well-timed access to business data.
We love Dynamics CRM but it's time to say bye since our own baby grew up. The whole CRM implementation project took 4 months of single person's labor time including data migration.
In the new major release of our platform we're clearly targeting deeper data analytics. AggreGate already outperforms the competition in its abilities to collect, store and visualize data. As for processing and analytics, it's now more comparable to Business Intelligence software rather than other IoT platforms, and requirements of this market are unprecedentedly high. With this release, we introduce machine learning, visual workflows and other modules designed for processing big data and getting in row with the best BI platforms.
The principal achievement of Release 5.5 is Machine Learning. It’s an instrument allowing data scientists to drill into time series streams and extremely large datasets in order to mine valuable knowledge. Trainable units that perform actual learning and scoring have so-called hyper parameters used by data scientists to fine-tune algorithm behaviour. Combined with workflows, machine learning module is a one-stop tool for predicting failures and optimizing operation of both physical assets and business services.
One more significant upgrade is Visual Workflows combining server-side logic with operator interactions. There can be unlimited number of concurrent event-initiated threads in any workflow. Workflows-based data processing and decision making algorithms may be implemented by anyone who doesn’t have even very basic scripting and programming language knowledge.
Graph Databases are currently gaining a lot of interest as a modern, robust and fast-growing Database Engine of the NoSQL family. They allow for you to represent complex interactions between your data in a much more natural form. Graph databases perform exceptionally well in path and structure analysis. One of the most intuitive fields of appliance is Configuration Management (and CMDBs).
Another considerable step forward is a new Report Editor. Jaspersoft® Studio, the leading report development software, is now bundled with AggreGate 5.5. Dozens of visual components, powerful data processing tools like expressions and queries along with rich export capabilities allow to embed highly interactive reports and analytics into any system.
AggreGate is a full-featured platform servicing as a foundation for custom turnkey solutions. Once a solution has been developed it should be rolled out to its end users. An effective way to replicate a solution is implementing a custom server plugin that incorporates specific system resources, such as alerts or dashboards. Resource Packs represent a new tool that automates and simplifies creation of resource plugins.
Other major improvements include:
Ladder Diagrams support
Statistics NoSQL Storage
Variable Access Performance Improvement
Embedded HTTP Server
A few more device drivers come with AggreGate 5.5: Ethernet/IP, XMPP, IEC 60870-5-104 Server.
Why do our partners complete highly tailored projects for the world’s largest telecom operators in a very short time?
AggreGate is a heart of any umbrella IT infrastructure solution. Having a unique underlying platform, it offers a huge set of data storage processing and visualization tools with many other management/monitoring solutions (SCADA/BMS, Access Control, etc.) They are not just integrated but share the same data model.
Being initially the driver of the IoT industry, smart city development technologies are rapidly progressing and becoming more and more sophisticated.
All cities are pretty unique, thus no fixed-function products will fit quickly changing demand even of single smallest community. What is required is a common flexible technology platform, and that's where AggreGate IoT Integration Platform perfectly fits the emerging market.
J'son & Partners Consulting company has included AggreGate IoT Platform into the research report called “AIoT (IoT in agriculture) current status and its evolvement forecast: international practices and conclusions for Russia” and called Tibbo Systems the leading company of Russian AIoT ecosystem.
The report contains research summary of AIoT current status in Russia and worldwide and its evolvement forecast. During project implementation, partner ecosystem is being formed. Such partners can be hardware vendors, telecom operators, IoT Platforms, system integrators, application developers, and end users. It is also pointed out that IoT platform is the kernel of such ecosystems.
Here is also the proof of the fact that precise agriculture and IoT technologies minimize operation costs and increase business efficiency.
Key IoT tasks and Russian agriculture digitalization are also mentioned, as well as Agtech development history, prospects, and constraining factors.
To sum up, it’s worth learning for everybody interested in IoT, and AIoT in particular.
The workspace offers a single-window UI to allow security officers to monitor physical security equipment operation, environment parameters, employee movements, as well as react promptly in case of an emergency situation.
The solution was presented to the President of Tatarstan region Mr. Rustam Minnikhanov at the Innopolis Venture Forum.
Our software offers fully functional monitoring solutions for healthcare organizations. Fast deployment, easy integration, and great usability guarantee quick troubleshooting to your healthcare IT teams.
AggreGate IoT Platform enables centralized monitoring and data aggregation for various wearable medical devices and mobile e-health applications. Intelligent Big Data processing algorithms allow detecting negative trends proactively, providing a strong foundation for building customized predictive medicine solutions.
In addition, choosing AggreGate solutions for your medical infrastructure monitoring, you get all types of industry-specific management.