Improve Your Decision Making Using IoT and ML


A phrase describing the plethora of devices, software and sensors developed in recent years that are capable of seizing, recording and transferring information in an automated way, Internet of Things or IoT is radically changing the data strategy of many businesses today.

To help businesses make better decisions in real time, new and exciting opportunities are being created by enormous amounts of data from wearable devices, sensors and other connected technologies. But, gathering all this data is half the solution. The other half of the solution lies in making this data actionable and how do you do that?

By combing Internet of Things (IoT) with Machine Learning (ML) technology.

How IoT and ML Combine to Improve Business Decision Making

How do you intelligently manage the overwhelming data created by the Internet of Things (IoT)? With Machine Learning.. A trend that has started in recent years and which is expected to continue in the coming years, the use of ML to manage the enormous amounts of data created by IoT provides valuable insights that businesses can use to make decisions and improve their operations.

It is expected that in the coming years, there will be billions of active connected devices and this will exponentially increase the data created by IoT. This is only going to make data management harder for businesses, unless they turn to machine learning.

Today, many companies including the big names such as Amazon and Netflix are benefiting by using ML to manage the data created by IoT. What are the exact benefits they’re enjoying?

Let’s have a look.

Elimination of Data Junk

Today, a plethora of information is available to businesses, which makes it difficult for them to distinguish the useful data from the ‘junk’. It’s virtually impossible for any human to quickly and accurately perform this function.

But, ML can do that for you as one of its main function is determining which data is useful, and which is not.  Even if the big data coming into your organization is unstructured and difficult to sort, machine learning can separate the useful data from the ‘junk’.

Recognition of Patterns

Say, you are provided with thousands of customer profiles with each profile containing the five-year buying history of the customer. Next, your manager asks you to identify patterns in the purchases—throughout the entire customers’ batch and not just by customer.

Sounds impossible?

Well, ML can do this for you and quickly to help you understand your customers and their decision making. With this information, you can determine the product, ad, or incentive your customer is most likely to respond to, which in turn can help you increase sales.

Eliminate Bias and Improve Decision Making

By providing information based on facts and data trends, IoT data managed by ML eliminates bias from business decisions, thus improving business decision making. Additionally, machine learning provides insights in real-time when the data is relevant and meaningful, which again aids the decision-making process.

IoT: Simplifying the Onboarding of Legacy Systems


The Internet of Things (IoT) is a collection of technological innovations which implements modern networking applications to improve everyday functions. IoT has amazing benefits in terms of improving our homes and offices by automating simple and mundane tasks that become repetitive for human resources. However, an important question that businesses face is what to do with their legacy systems which are already in place.

IoT solutions have the answer to this question. With the right application, IoT can on board any legacy system through a simplification process. Here are a few points that describe how IoT can simplify this process:

Understanding Legacy Systems

A legacy system is best defined as an old computer system, which may not be supported by the current set of equipment and services. However, all systems develop from their earlier counterparts. One problem associated with technology solutions are the excessive costs required to install modern sensors and machines. However, solutions like IoTSense provide out of the box support for legacy protocols; streamlining the communication and reducing costs of replacing or modernizing the legacy devices helping you scale up exponentially.

Using Open Source Software

With the use of IoT solutions that employ open source software, it is possible to understand how a legacy system operates and simply create a customized program for implementing it in a modern, IoT based industrial solution. A software tool that can receive further plug-ins certainly makes it easier to include legacy systems within the overall solution. A single application can be used globally in such an environment as well.

Once an open source solution is produced for a legacy system, it can be used in a variety of situations.

Integrated Scaling

Another problem that businesses face with legacy systems is when they are looking to scale their operations. As they can then create a mix of new and old computer systems that provide support, it can be difficult to work with them on a similar level. A smart IoT solution can bridge the gap between the capabilities of both systems and allows companies to perform integrated scaling and expansion.


The ideal IoT solution ensures that you can take legacy systems on board while ensuring that the security of your data remains at the highest level. This is possible when an IoT solution connects using legacy protocols and extracts the data. While sending data to cloud, the security standards asked by the respective cloud providers is used.

If you are struggling with legacy systems in your business and want to move ahead, our IoT solutions IoTSense will help you easily integrate them into a modern data processing and analytics production system. This will help you gain a competitive edge that you are looking for!

How is IoT Making your Product Better?


The Internet of Things (IoT) is an excellent innovation and is helping several businesses. While you may believe that your business produces a specific physical product, implementing IoT solutions can certainly improve several aspects of your product. Here, we describe you  diverse ways in which you can implement solutions like IoTSense to help you improve your product.

Better Industrial Control

IoT solutions can easily work with industrial machines and improve their ability to carry out the required production according to available order information. This improves your control over the output of your installed machines and allows for better coordination practices. Device management is possible with a tool like IoTSense which can gather data from multiple data sources and then use it to create the valuable information that you need to do well in your business.


IoT solutions are excellent in improving your product because they allow you to scale up with increasing business demands. This ensures that you can maintain the quality of your business products by recording data with a cloud system that can generate the required statistics in maintaining great control over the production.

IoT business solutions are excellent for creating a webbed environment of support services. These services allow companies to create a structure which is ready to provide product support and problem solving regardless of the volume of the sales. With the IoT solutions capable of offering data and analytical support in a consistent manner, you can ensure that you constantly improve your product even when you are scaling your business at any time.

Improved Efficiency

Efficiency is important for improving any product. This is possible when you employ IoT solutions like IoTSense that can improve multiple aspects of your business.

It can provide information about business processes, which ultimately leads to performing automation and improving them in a continuous manner.

The presence of improved efficiency is also the key in terms of maximizing the return on investment (ROI) in any business and ensuring that you are performing at an optimum level. The smart device management and the collection of information on a single platform are key features of IoT solutions that will help you raise the efficiency standards of your business product.


IoT software solutions like IoTSense give you access to improved analytical information. This will allow your product to improve through a dedicated research and development process. With access to real-time information through a dedicated dashboard, it is possible to quickly identify problem areas and make the necessary improvements.

The analytics further help when they are combined with IoT solutions that allow the use of edge computing. It is a system that uses decentralized processing to improve organizational performance in the field of the intended business function.

Visualize your Progress with IoTSense Analytics


Visualize your Progress with IoTSense Analytics

Analyzing a large amount of data and leveraging it to visualize progress, as well as making policies based on the findings, is basically what places an organization ahead of the competition these days. This is because accumulated data is priceless, and when processed and analyzed to perfection, can reveal tremendously beneficial details which can be capitalized on.

IoTSense Analytics: Efficient Data Analysis within the Internet of Things

IoTSense is one of the many IoT platforms currently available to the public, with many features that allows  quick and easy analysis of data throughout a network. This allows users of a network to not only see all the data that has been accumulated because of continuous function, but also leverage it to see how efficient the function is.

The visualization of progress aids in improvement of all the processes within the system. Since the data received through platform such as IoTSense is analyzed in real time, the progression of data is also recorded; in order to reveal which improvement based step needs to be taken.

Benefits of IoTSense towards Data Leveraging and Process Improvement

Following are some of the advanced analytics features which can be utilized for the visualization of progress within a network.

  • A local dashboard enables users to have all of the analytics information within reach, through an active interface that clearly defines all the aspects of the framework which needs to be analyzed.
  • Easy configuration of the analytics parameters allows the visualization of very specific performance indicators.
  • The real-time analytics feature allows for in-depth analysis of all the performance parameters in real time, thereby letting the responsible parties adjust functions and take measures to align performance with pre-set goals.

Connectivity Options Benefitting Visualization

A highly valuable and often ignored aspect of an IoT framework is the plethora of connectivity options that one has at their disposal; all which aid in active visualization of progress. Currently, variety is of utmost importance, especially when it comes to visualization in a cross-platform environment, where seamless connections are necessary to view practical progress through several connectivity media.

Multiple connectivity options also benefit with real-time monitoring of performance, since multiple performance parameters can be accessed and monitored at the same time, without resorting to separate searches for each parameter. All monitoring points could be connected to a local dashboard, through which multiple divisions can be visualized, to actively gauge progress.


An IoT platform such as IoTSense can make the visualization of progress a breeze through the plethora of features which are optimized for this very purpose, as well as the multi-channel connectivity. Since it unites all performance parameters under one roof, it is easy for a single user to see how the performance of the entire network measures up against the decided goals, for better performance in the future.

Computer Vision in IoT Electronic Observation Tools


Computer Vision in IoT Electronic Observation Tools

The realm of computer vision is steadily progressing, with the advent of technologies such as extreme resolution imaging and augmented reality.

Computer systems, in this day and age, are able to recognize and analyze patterns and points better than ever before, and a lot of that has to do with the growing demands of the global security enterprise, as well as the entertainment industry. The latter is utilizing computer vision more widely and companies producing entertainment based technologies are leveraging other advancements such as AI and augmented reality to better their functionality while offering the customer more.

However, it is the security industry that is really expanding the horizons of what is possible in terms of surveillance capability.

Computer Vision in Surveillance

The application of computer vision in surveillance comes as no surprise, since security and surveillance cameras need to identify and analyze patterns and markers more efficiently, in order to function better. This development and the integration of computer vision in surveillance as a whole, can be attributed to security agencies and companies who consistently demand quicker and more efficient identification and pattern recognition.

The IoT-based Application

Applying the concepts of computer vision can prove to be very effective, however, applying them in an IoT based network, is quite another. It is considerably more effective, since M2M communication can then be leveraged, and the identification capabilities can be increased exponentially.


Following are some of the applications of computer vision inside an IoT based framework:

  • General Manufacturing: Not only can computer vision be applied to observe every aspect of the manufacturing process, but the principles can be used for procedural surveillance and observation of the supply chain.
  • Plant Growth Monitoring: The growth of valuable plants, used for a variety of medicinal and research-based purposes, can be done in real time, throughout the developmental stages.
  • Traffic Monitoring: The ebb and flow of traffic can be managed and controlled through a machine-based network, which evaluates congestion potential and adjusts the flow to actively prevent both jams and accidents.

The Deep Learning Advantage

Many gaps in the surveillance world were filled with the advent of deep-learning systems, which used algorithms that allowed machine intelligence to be multiplied exponentially, over time. The best aspect of these algorithms was that they could potentially be applied to any number of systems, from the artificial intelligence in video games, to security systems that learn typical patterns over time, and highlighted them in real time, on the very next occurrence.

Also, deep learning algorithms, when applied to IoT-based frameworks, already demonstrated accuracy of judgment better than the human competition. This is a part of computer vision that, when engineered specifically for the surveillance industry, could bolster the possibilities for the industry itself.

Power Management with Connected Buildings


Power Management with Connected Buildings

We are obsessed towards finding cost savings and optimizing performance when it comes to our work, home or school. But, due to reasons unknown we often neglect the very walls we have around us. Going along the lines of better and smarter buildings, IoT has given us the concept of smart buildings. A smart building basically uses data analytics and the art of connectivity to automatically take actions for solving real time problems that can arise at anytime. From automatically adjusting lighting levels based on the occupancy within a room to optimizing the flow of people passing through a facility, smart buildings can achieve and drive smarter outcomes.

The concept of building management has enhanced ever since the origin of connected buildings. One of the aspects of building management that will benefit due to these connected buildings is power management. The American Council for an Energy Efficient Economy (ACEEE) reported that buildings could save up to $60 billion if the efforts towards power management were increased by a mere 1-4%.

With power overuse and depletion at stake, it is high time we took power management with connected buildings seriously. It is expected that the U.S alone could save more than 20 per cent of its projected electricity usage for 2030 by implementing smart power management methods.

This prediction relies heavily on the use of smart appliances and equipment that utilize the concepts of IoT to create a building management concept that could lead the way into the future.

The 3 technologies mentioned below could really go a long way in leveraging power management within connected buildings for the better:

  1. Advanced energy management systems: This automated concept of fault detection and real time diagnoses helps newer systems in reducing O&M costs and downtimes. This would simply add to the energy savings and optimize equipment setpoints.
  2. Smart Lighting: This technology implements the concept of IoT in full force to leverage efforts made for power management. The system would not only turn lights on & off at different times of the day depending on the natural light levels, but also performs a comparative analysis on evaluating the impact of HVAC energy use on power consumption. Besides just evaluating the use of the HVAC system, smart lighting within a smart building will work according to the occupancy levels within a room or place. The occupancy levels will drive the lighting levels deemed feasible for the space.
  3. Smart HVAC: Tying HVAC into the energy management setup for the building could maximize savings. Control strategies for HVAC systems can efficiently customize air conditioning based on data pertaining to the preferences of the people living inside.

Most organizations are built upon growth and progress. With smart buildings, the same notion of growth and progress is transferred to our facilities. Our buildings can now carry our own DNA to be lean, autonomous and smart.

Think Horizontal for IoT Expansion


Think Horizontal for IoT Expansion

The Internet of Things (IoT) is a great concept and is an emerging application of the available processing and networking technologies. We are seeing the everyday use of devices that have embedded networking functionality. The ability to send and receive data allows these IoT devices to communicate with each other.

One of the amazing applications that the IoT concept can cover is the ability to provide horizontal functionality. We commonly find that embedded devices can easily work under a vertical system, where a defined hierarchy ensures that a central system may provide the control for all connected devices. However, there are applications where we may require horizontal functionality.

Horizontal Application

This is a new avenue that was seldom explored during the early days of IoT. With new technology companies emerging in IoT, you need to think horizontal for the ideal IoT expansion. Remember, horizontal expansion occurs when we think about connecting devices that are present on the same level.

Horizontal expansion certainly has the benefit of allowing a business to make use of the modern smart networks. With multiple devices connecting different aspects of the business, the use of consistently improving singular functionality can generate a greater value for business. IoT expansion using horizontal techniques is possible when more smart devices can be employed to improve the functions that a company performs.

This working structure may be found when dealing with large enterprise applications. An application which can work by taking input from multiple points to provide the ideal functionality for a user is the ideal reason for producing an IoT expansion in the horizontal direction.

There are several companies that may perform work using different locations. Their performance can certainly improve with the help of smart devices that all work together as a singular system and ensure that business expansion is possible with the use of an ideal IoT expansion. This expansion has the capacity to give companies an edge that they need. Horizontal expansion is certainly an addition to the current capabilities of IoT applications.

The Fourth Layer

A horizontal expansion in the internet of things may provide a fourth layer to the current application. The first three layers consist of media, network, and application. The first layer contains the devices; the second layer discusses the network connection between the devices; and the third layer discusses the functionality, which may be controlled by a central device.

Horizontal IoT expansion allows the use of agnostic practices. The data can be identified as unique, regardless of the application in which it is employed. This allows the use of standardized practices that can create both generic and specific solutions for IoT applications. Horizontal expansion has the capacity to increase the number of smart devices that can be used in various parts of a company to generate more data for singular applications.

Adding horizontal expansion ensures that we can employ multiple IoT sets to perform individual tasks to achieve a singular result for a user of IoT technology. Think horizontal to truly enhance the advantages you gain from an IoT application!

Unifying Cloud IoT Solutions with Edge


Unifying Cloud IoT Solutions with Edge

Cloud-based IoT Solutions

Cloud highly efficient and does not require an extensive infrastructure, it can be easily to manage. Bring cloud-based IoT solutions into the mix, and you have a very strong network, with very few connectivity issues, and almost seamless sharing of data and performance of processes.

Potential Weaknesses within the Cloud Computing Architecture

As good as cloud computing may be in terms of functionality and efficiency, it is not always the most proficient when it comes to preservation of security. As it is a centralized solution, which in turn relies on stable connection for as many data storage and processing centers there are, it can be prone to failure associated with infrastructure failure due to connection issues and malignant outside interference.

A connection issue could potentially halt operations, since computing power is centralized, and if the server is down, then the entire network cannot function.

3 Reasons to Unify Cloud IoT Solutions with Edge Sync Management

Following are some reasons why Cloud IoT solutions should be unified with edge sync management.

  • Preservation of Privacy: When some data is accessed within an IoT network, there are myriad chances of the privacy of that data being compromised. When the data is processed on the spot, it is better protected since not many other users on the network have access to said data.
  • Reduction of Latency: Cloud IoT solutions can implement acquired learning on any number of connected systems, or even throughout the cloud network. Edge sync management can be implemented alongside, which will result in more complex tasks being performed off the high traffic areas, leading to a significant reduction in latency.
  • Increased Awareness of Connectivity Issues: Since edge sync management increases the efficiency of the network to a significant degree, it will be beneficial to implement it across a given network, along with the cloud IoT solutions. There are many connectivity issues that rise in such a network, and the more distant a process in from a problematic area, the more efficient it will be.
  • Multiple Sources Distribute Security and Computing: The biggest advantage of edge computing for a cloud-based IoT network is the distribution of security and computing power. This leaves other members of the network immune to connection stress, as well as security issues, since each user must manage both. On the practical side of things, this makes a very positive user experience, since their connection and time within the network is not affected by either integral or external influences.

In conclusion, it is very viable to fuse cloud-based IoT solutions with edge sync management, for across-the-board success. Almost all manner of cloud-based networks, be they social or official, can use the marriage of effective edge sync management with cloud IoT solutions.

The Smart Future of Oil and Gas Industry


The Smart Future of Oil and Gas Industry

The emergence of disruptive technologies, like the Internet of Things (IoT) and blockchain,havebrought change to the way the world works and the oil and gas industry is a field which is no stranger to the innovations to them. The core focus of the industry has always been on making the extraction and refining process better. However, the technologies pertaining to processespost production have been lacking.

The supply chain the industry has traditionally relied on has too many bottlenecks. Fortunately, two emerging technologies, the IoT and Blockchain offer great opportunities to automate many processes across the supply chain.  However, both have had very little impact on the oil and gas industry thus far. However, they have done enough to present leaders in the industry enough to gauge its potential in the industry.

Oil and Gas companies have been slow in integrating new technologies that can aid the trading, procurement and supply chain aspect of the industries until recently. For instance, different aspects of blockchain technology have come to light that can benefit the oil and gas industry. Transparency is something blockchain enables through its basic design. Having shared information on a blockchain within joint operational agreements can essentially eliminate the need for third party reconciliation between companies. That will also result in reduced cost of compliance.

Furthermore, blockchain technology can enable better cyber security measures for the IoT that gather information critical for operations. It can allow for the storage of sensitive and critical data in multiple places instead of a singular source which increases the data protection capabilities augmented by the use of encrypted systems. The technology, though still in its nascent stages, holds potential for industries across the board and can provide previously unprecedented efficacy to the oil and gas industry that can help it ride the volatility in fossil fuel prices smoothly.

How Oil and Gas can Leverage Artificial Intelligence

There are a few ways through which the oil and gas sector can become smart by implementing Artificial methods of intelligence.

Planning and Forecasting

Deep machine learning can increase the awareness of trends to drive future investment decisions on a macro scale. Economic patterns in state and other weather predictions can be assessed to determine where the investments should be centered.

Eliminate Costly Drilling Risks

Drilling is a risky and expensive part of the whole process. The application of AI in planning and implementation stages can significantly decrease the risk associated with this activity. Additionally, geoscientists can also evaluate factors such as rate of penetration to find out which drilling tactic would be best for the site. There are many factors that are taken into consideration during this process. Some of these factors include thermal gradients, strata permeability and seismic vibrations. AI can optimize the whole operation by driving decisions related to the speed and direction.

The current wave towards smart methods in the oil and gas sector are aided by investor interest as many investors aim to increase efficiency through the use of smart technology.

Smart Technology in the Automotive Industry


Smart Technology in the Automotive Industry

Smart vehicles are becoming more common each day, and the IoT integration network concerning the automotive industry looks to be mainstream by the end of next year.

The Advent of Advanced Centrally-Linked Automobiles

After successful implementation with home management systems and smart hand-held devices, it is no surprise that cars are the next frontier to be enveloped by the IoT.

The public transport industry is also looking to capitalize on the trend, and have buses, trains and taxis interconnected within a common network.

Benefits of IoT Integration in the Automotive Industry

Following are some of the benefits that car manufacturers and drivers can expect with the IoT integration in the automotive industry.

Manufacturer-centric benefits:

  • Hardware-based, tethered linkage would allow third party applications and software to enrich the driving experience, therefore leading to better profits.
  • Internal embedded linkage would allow the car to be self-sufficient, negating the need for external third-party software for infotainment facilitation.
  • Self-driving cars will be refined and officially produced due to increasing IoT integration.

Driver-centric benefits:

  • Fulfilling and rich driving experience with application accessibility in tethered connections.
  • Increased driver ease due to extensive electronic aids within the car’s software infrastructure.
  • Constant Google and affiliated application accessibility, which provides entertainment and driver assistance on the go.
  • Real-time, network software-based monitoring of vehicle performance and condition, letting drivers feel less burdened.

Practical Applications and Existing Advancements

The applications of smart vehicular technology started with the military-industrial realm, and then entered the public zone. Cars, as mentioned earlier, were among the first ‘devices’ to start utilizing autonomy as a means of aiding the process of driving, and potentially enhancing driver experience.

Cars are now learning patterns and common traits of the driver, the routes and even the terrain, to provide a better driving experience and enhance the transportation system as a whole, with greater efficiency, real time updates, and data transfer across and from networks,

Easier Commuting, Endless Possibilities

The car of the future is bound to be connected to a network, which it must be if the manufacturers are to keep up with the technological revolution, and provide a better, all-inclusive and immersive driving experience. At present, cars are already benefiting from Google’s mapping system, which allows for better routes to be picked and potential ‘roadblocks’ to be avoided. The  sky is the limit for the automotive industry, once smart technology is factored in.