In the IoT world, the analysis of data allows companies to improve business processes or foster innovation.
As we move from an M2M world to the Internet of Things (IoT) we will increasingly see the value of aggregating and analyzing data from various devices – some machines, some personal devices like smartphones. The aggregation and systematic use of these data is one of the M2M-to-IoT transitions we described in a prior blog post entitled Progression from M2M to the Internet of Things: an introductory blog.
According to Wikipedia, “analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.” By using various predictive models and statistical techniques, analytics can help optimize decisions. Read more…
With 1.8 billion households worldwide in 2012, there are many growth opportunities in the smart home sector.
Do you want your appliances connected to a WiFi or other network in your home? Do you want a video-based security and surveillance solution that can identify the people who live in your home or are possible intruders? Do you want a system that monitors for broken water pipes when you’re away on vacation?
There are myriad solutions that enable the smart home and there is no end in the creativity shown by product and service vendors in offering these types of solutions. With 1.8 billion households worldwide in 2012, there are many growth opportunities in this sector. But the trick is finding target segments for these solutions, creating easy-to-use solutions and offering solutions at prices that are reasonable enough to attract the target segments. Read more…
In an earlier blog post, our guest author Jim Morrish highlighted the emergence of the M2M / IoT Application Platform. He described these as M2M platforms recast for the age of the Internet of Things.
In this blog post I explore the ideal functionality of M2M / IoT Application Platforms. The key purpose of such a platform is to support applications which encompass both M2M and IoT aspects, but what does that really mean? What is it that an M2M / IoT Application Platform offers that M2M platforms do not?
We think that the key areas in which an M2M / IoT Application Platform differs from the more ‘traditional’ M2M platform environment really revolve around IoT enabling capabilities, and we think that these will become the basis of competition in the M2M / IoT Application Platform space. The below graphic displays what we consider as IoT enabling and IoT supporting capabilities.
Ideal functionality of M2M / IoT Application Platforms [Source: Machina Research, 2013]
Our guest author Jim Morrish is a Director and Founder of Machina Research, the technology research and consulting firm focused on emerging opportunities associated with new forms of connected devices. He has over 20 years experience in the telecoms industry, including strategy consulting, operations management and research. He has worked on-site in more than 25 countries through Europe, Asia, Africa, the Middle East and the Americas. He has a MA in Mathematics, specialising in logic, from the University of Oxford. Follow Jim on Twitter: @Machina Research
M2M is a label that has been attached to a concept that has been around in the telco industry for years. In fact, the roots of M2M extend back over several decades and include basic fleet management solutions and SCADA (supervisory control and data acquisition) solutions. Traditionally, M2M solutions have been conceived and deployed as ‘stovepipe’ (or standalone) solutions with the aim of improving (or enabling) a specific process, and without consideration of how these solutions might one day be integrated into a wider business context.
In the early days of M2M, any aspiring application developers would have had to face up to the challenge of creating an entire solution stack to support their intended application. Relatively few of the components needed to develop specific applications were available ‘off the shelf’, and relatively few solution components could be shared between different applications. In all, an early M2M developer would have had to contend with three key elements of an overall M2M solution: Devices, M2M Application Environment, and M2M Application Logic. That’s a tall order, and has acted to slow the adoption of M2M to IoT solutions. However, in recent years a range of different kinds of M2M platforms have emerged to speed the development and deployment of (generally still stove-pipe) M2M applications. And, as a result the M2M market has grown into a significant opportunity.
Traditional M2M markets are changing to support an emerging IoT world (Source: Machina Research, 2013)
Remote maintenance solutions help reducing travel and personnel costs while improving customer service by offering faster response times.
Remote maintenance services have been used in the manufacturing industry for many years to maintain spatially distributed machines and equipment. Using a dedicated line, service engineers can establish a connection to a machine and access its control system. Depending on the available transmission mode and access rights, the engineer can provide passive assistance to on-site machine operators or even take active control of the system. The benefits are obvious: remote maintenance slashes travel and personnel costs while improving customer service by offering faster response times.
This recent surge in demand has fueled a boom in the availability of remote maintenance software for industry applications. However, many of these programs lack the necessary flexibility and “intelligence.” Typically, a separate PC or desktop environment must be set up for each active machine. In addition, the applications are not usually integrated in the existing system environment, so the data they collect cannot be incorporated into these systems unless it is entered manually or copied from a USB stick. However, these problems need not exist as technology already provides everything needed to address these issues.
Today in an era of climate change and expensive energy production resources, we look for new ways to manage electricity.
Energy conservation and management has been around as long as humans have used energy sources. In summer months, pioneers chopped enough wood for fireplaces and cooking hearths to last all winter. Mill owners would engage in peak production when water levels were high enough to power their water-fed mills. And today in an era of climate change and expensive energy production resources, we look for new ways to manage electricity. As we move to an Internet of Things (IoT) world, we will see greater adoption of energy management solutions.
There are various types of energy management applications. All of these applications are in use today, although some have found higher levels of adoption than others. Read more…
Some amount of security and surveillance is necessary in today’s world (Photo: Bosch)
Security – precautions taken to guard against crime, attack, sabotage, espionage, etc.
Security and surveillance has become a common facet of business. There are dangers in the world: some are personal dangers, others are dangers or risks associated with assets. While there has been much recent debate about the appropriate use and amount of surveillance, it is fair to say that some amount of security and surveillance is necessary in today’s world.
Security and surveillance solutions include everything from the most simple home monitoring systems and burglar alarms, to high-definition, motion-detecting cameras and retina scanning security solutions. Various forms of connectivity – both fixed-line and wireless – enable a basic type of M2M security solutions. However, when data from the solutions are aggregated and analyzed to predict behavior or thwart crimes, and we are able to access these data on common platforms and devices – including mobile devices – we have entered the world of the Internet of Things (IoT). I described this type of change from an M2M to an IoT world in a prior blog post entitled Progression from M2M to the Internet of Things: an introductory blog. Read more…
Consumers have traditionally relied on bringing their own devices to remain connected while in their cars.
The passenger automobile is one of the venues where there is tremendous opportunity for adding connectivity. You can use your mobile feature phone in the car, but that feels a little like retrofitting an old rotary-dial phone into your 21st-century home. In both, the developed and emerging worlds, it’s common for commuters to spend 1-2 hours per day driving in their automobiles to work. Isn’t it odd that new automobiles with all their computer componentry are not ubiquitously connected? What does the world of connected cars have in store for us? Read more…
Connectivity is necessary, but not sufficient for the Internet of Things (IoT). As I discussed in an earlier blog posting, connectivity is one of the elements of an IoT solution: it’s the part that provides LAN and/or WAN communications between the hardware layer (equipment) and the application layer. See Figure 1.
Figure 1: Same layers, two worlds: M2M and IoT supply chains in comparison [Source: Analysys Mason, 2012]
I’ve often wondered why I need to change my automobile’s motor oil every 3,500 miles or 3 months, whichever comes first. Maybe I’m one of the few people left in the world who still enjoys changing his own oil. But it’s often concerned me that maybe a mileage- or time-based maintenance schedule wastes lots of valuable resources like oil; aluminium and metals for fabricating the new oil filter; plastic for making the new jug of oil; and energy for the recycling facility that takes my dirty motor oil, strips all the impurities from it and recycles it.
Maybe I don’t really need to change the oil that often. Maybe the metrics which determine when I should change the oil – in this case either vehicle mileage or time – aren’t the best predictors of my car’s optimal maintenance schedule. What if there were sensors on my red 1966 Ford Mustang convertible (V8, 289 cubic inch engine, 2-barrel carburettor, for those curious) that would tell me when I need to change the oil. And what if those sensors were collecting data from the oil filter, the valves, the pistons and the exhaust to find anomalies that are better predictors of when I should change my oil to prevent deterioration of my car.
Predictive maintenance is one such IoT/M2M solution that helps lower operating and capital costs by facilitating proactive servicing and repair of assets, while allowing the more efficient use of repair resources – both human labor and replacement products. See Fig. 1.
Figure 1: Traditional maintenance scheduling versus predictive maintenance for assets [Source: Analysys Mason, 2013]