5 min read2018 has been a great year, the team has been busy planning and [...]
2018 has been a great year, the team has been busy planning and productizing new product features, and enhancing existing ones to better serve you – our clients and partners!
Worried that you missed an important product feature announcement? Fear not! The following is a recap of what happened in 2018 and upcoming roadmap highlights for 2019.
Mnubo’s SmartObjects Platform
Mnubo’s Customer Experience Application helps manufacturer better serve clients by understanding customer engagement, satisfaction and behaviour. We believe that in order to reap the full potential and benefits of analytics, it’s necessary to break the silos and work together as a team.
With this in mind we’ve come up with new ‘Market Success Dashboard’ that empowers product managers, service providers, marketing teams, sales team, and many others with real-time insights that will help them achieve their business and financial KPIs.
Some key insights derived from Customer Experience Application include:
With Mnubo’s Asset Health Application, manufacturers can improve their bottom line by better understanding the health/performance of their assets. It comes with a portfolio of dashboards that are geared towards the service and support teams to enable them to reduce operational costs associated with maintaining equipment.
Some key insights used in the Asset Health Dashboard include:
Mnubo’s Asset Health Dashboard
‘Scoring and Ranking’ is a new native library that allows you to score, rank and compare products and/or customer behaviour (performance, usage, security, etc) over time. With just a few clicks, it will answer questions like:
Find out how service teams leverage Mnubo’s Scoring Library to improve service efficiency and reduce cost of maintenance.
This insight library was designed specifically for ‘non-coders’ to quickly and easily explore their IoT data for answers to critical business questions. With Event Explorer, you can automatically crawl an IoT data set in its entirety, or any subset, and highlight the distribution of all events (scheduled, unscheduled, mobile, faults, rules-driven, personal assistant, etc.) and the correlation between one another.
Below are a few of its applications:
Using Event Explorer Library to see the daily distribution of event counts in the selected time period.
Find out how the Event Explorer helps uncover anomalies in data.
The Anomaly Detection library will help you uncover univariate and multivariate anomalies in time-series data. It is used to identify data points that do not conform to an expected pattern in a dataset.
Some examples include:
Analyzing faults in HVAC data using Anomaly Detection Library.
The Digital Twin lets you explore the digital representation of your physical assets. It allows you to see the current state of your devices and all the events and time-series that were posted by the device.
Using the Digital Twin Library to explore and and analyze the digital replica of the assets to find faults, abnormal behaviors, etc.
The AIoT studio empowers Data Scientists with the appropriate tools to overcome the challenges of launching and managing the full life-cycle of a new IoT project.
AIoT Studio is a fully managed IoT-focused AI/ML studio that allows you to develop, train/maintain, deploy, and run AI/ML models as well as ad-hoc algorithms against live streaming data. It unscrambles and abstracts the complexity of building and maintaining the infrastructure required to power production ready AI/ML at scale.
Develop, train, deploy and run your own AI/ML model using AIoT Studio
With our expansion into the Japanese market, SmartObjects is now fully available in Japanese.
Do you want to control which stakeholders have access and editing rights to each dashboard? Mnubo’s new role manager, Viewer, allows administrators to grant or deny access to Custom Dashboards and External Applications, granting the Viewers with read-only rights.
Mnubo’s new generic Partner Connection layer expedites the data model mapping and data streaming of content already stored in any of our partners’ solution; this layer abstracts many data messaging protocols used in IoT including MQTT, Webhooks, Kinesis, Node-RED, etc.
Customers storing very large volumes of data and/or requesting that older archives be available at query time (even if not queried often and/or when these archives are used to train AI/ML models), now have the option of storing any data after a cut-off size at a lower cost.
In the coming months, we’ll be releasing additional product features to help customers develop a deeper and greater understanding of their products.
New operational efficiency dashboards will be deployed that empower the service, customer support and quality control teams with better visibility throughout the products’ connected life cycle.
Next, updating our existing data model with advanced in stream annotation to automatically convert telemetry into semantically rich events – e.g. for an HVACR data, log a fault event when temperature higher than X and humidity higher than Y.
For our customers in the insurance industry, we are coming up with new financial packages that they could share with their clients to insure uptime, increase production, and improve efficiency gains.
And finally, working rigorously to ensure SmartObjects supports edge analytics to alleviate network bandwidth limitations, address security concerns, and extend predictive capabilities by quickly turning data-based insights into actions.