Archive for the ‘sensors’ Tag

Internet of Things can grow Customer Lifetime Value   Leave a comment

Customer lifetime value (CLV) is an important metric as it captures the revenue potential of each customer relationship over their lifespan with a company. Higher CLVs lead to greater profits for the enterprise, and now, with the rise of potentially billions of cloud connected sensors and smart devices collectively known as the Internet of Things (IoT), there are more opportunities than ever before to grow both.

The IoT relies on sensors and machine-to-machine (M2M) communications to produce data on a variety of subjects. Translating that data into more rewarding customer experiences is one of the most significant opportunities that comes with the Internet of Things. Here are three ways any enterprise can mine IoT data to cultivate deeper customer connections and generate higher per-customer revenues.

1.Monetize IoT Data by Expanding Offerings:

One way to improve Customer lifetime value CLV is to use data created by IoT devices to give existing customers new ways to consume products and services — and more reasons to remain loyal. Adding IoT-driven services to an existing product catalog can help marketers meet fast-changing customer demands and keep competitors at bay.

For example, in the offline world, auto insurers like Progressive are accommodating their cost-conscious customers by offering them new pay-as-you-drive policies where rates are based on the miles actually driven. Mileage is tracked and sent to the insurance carrier through a small IoT-connected dashboard plug-in. Consumption-based policies such as these can lower premiums by as much as 50 percent – a powerful incentive for insurance customers to stay put.

Cable TV providers are especially adept at the repackaging game. It’s how they fend off subscriber churn. Earlier, they expanded beyond TV with triple play packages that added Internet and phone services to the mix. With the advent of IoT, they’ve now added another: smart-home monitoring. These systems combine motion sensors, cameras, smart locks and brainy thermostats that allow cable customers to remotely manage hearth and home from anywhere. Subscribers who sign up for these services view them as a convenience they can just add to their existing bill. That’s exactly the mindset companies want their customers to have if the objective is to increase CLV.

In the online realm, MyFitnessPal, the world’s top online health and nutrition membership community, is embracing IoT to make it even easier for its more than 80 million members to reach their goals. They can now add personal data from their favorite wearable IoT fitness gadgets like Fitbit and Jawbone to the other health information they track on MyFitnessPal. Providing an in-demand service like this pays off for the website, even though its CLV is difficult to pin down because the site is free to join and ad-supported. Earlier this year, sportswear maker Under Armour purchased MyFitnessPal for $475 million. Clearly, its goal is not only to monetize the site, but also to tie it into its own sales of IoT trackers, including computerized performance wear.

2. Improve your website experience to deepen engagement:

For any company that sells online, one of the most obvious means for growing CLV is to improve how visitors engage with the website. Data gleaned through the IoT can provide a clue. Several vendors offer sophisticated analytics that can help brands identify site issues that may be causing lost sales and missed connections. Some companies uses IoT advancements in M2M learning and powerful algorithms to assess the way visitors interact with websites. The solution tracks subtle variations in customer clicks, scrolls and mouse movements in real-time so designers/marketers can better understand both behavior and intention.

3. Get personal to boost customer satisfaction and loyalty:

Relying on the IoT to make a website more personal is only the beginning. The truth is, the technology serves up personalization opportunities in spades. An expanding universe of smart sensors and devices
generate continuous streams of personalized, real-time data on just about anything people want to monitor and manage — from heartbeats, footsteps and sleep cycles to inventory levels, shipments in transit and medical diagnostic equipment.

Consider online streaming TV pioneer Netflix. It’s made a science of personalization, due in part to its
reliance on intricate M2M processing. For example, each day, it tracks millions of viewing streams from its customers. From this data, it not only offers customer specific viewing recommendations based on predictive analytics, but also shows individual subscribers exactly what they’ve already watched and even where they paused a particular show, no matter what device they use when they return.
Personalized experiences like these are a key reason behind Netflix’s outlandish success.

Indeed, endless digital rivers of IoT data hold a veritable treasure trove of information brands can harness to transform customer satisfaction and increase CLV. That’s because most IoT products and services leave a digital trail that reveals details about the way customers use and interact with them. Consumption data provides an unprecedented view into customer behaviors, preferences and usage patterns. With these insights, it is possible to produce perfectly timed, spoton offers and incentives that
customers increasingly expect.


Wireless sensor networks in the Internet of Things   Leave a comment

As the market for the Internet of Things starts to take shape, the role of wireless sensor networks in enabling a range of new applications, has started to take centre stage, with demand growing for extremely low power solutions.

While sensor-based networks for monitoring and control are not new concepts, demand for wireless implementations – previously limited to just a few niche markets – is set to grow as companies look to bene8t from the combination of installation simplicity and low-cost.

Wireless systems need to consume as little power as possible and next generation networks are being developed where batteries require little maintenance over the application’s life time. As an alternative, there is also a focus on energy harvesting to provide the necessary power, removing the need for batteries completely.

Energy harvesting is becoming  more attractive because it doesn’t require continual recharging and does away with the need for communication or power wires. The challenge with its deployment comes when it needs to be located in more challenging environments and especially when power needs to be stored. If you have to incorporate temporary storage capabilities in a design, then the application will, as a necessity, become far more complicated – cost, as a result, then becomes a more important issue, especially if you are distributing hundreds or thousands of sensors.

Applications have different power requirements. A door lock, for example, may only have to report back every hour or when something happens. As a result the power requirements will be low. By comparison, some wearable devices, such as the Apple Watch, consume far too much power to deploy a harvesting solution. The challenge is being able to develop an MCU that is capable of driving an application but which comes with very low power consumption. When powering sensors is that energy harvesting may only be able to supply as little as 10μA ontinuously, especially if the energy source is a small solar panel.

By contrast, a microcontroller executing code will have power requirements hundreds or thousands times greater. As a result, application designs will need to be able to fully leverage various sleep modes and should be designed with a view to putting the application into sleep mode as much as is possible.

Most applications will come with a variety of preset operating modes, so the embedded microcontroller can, for example, be put into a ‘sleep’ or enter an extreme, low-power ‘standby’ mode in between different data samples. If the microcontroller collects sufficient data, it can then switch to a ‘fully on’ mode, where it is awake and running at maximum operating speed. This will require the microcontroller to receive some kind of wake-up event, which could be triggered by an external event or by internal processor activity.

From an ‘always on’ mode to a ‘sleep’ or ‘standby’ mode, where memory stays powered, or a ‘deep sleep’ mode, where the memory is powered down for maximum power savings, the choice of a microcontroller’s power modes can have a significant impact on the overall power requirements of an application.

The problem with energy harvesting solutions is the energy output might be too low to power up the MCU. Starting an MCU  will require a lot of current; more than the energy harvesting component can provide. As a result, you need to deploy a mechanism whereby the MCU will only start-up when sufficient energy has been stored, usually a capacitor to store the energy and a comparator capable of detecting the amount of power available.

Once the application has powered up, it can then return to a more suitable power mode. It means the application has greater stability.

Accurate timing is needed to ensure the wireless sensor transmits information during a predefined assigned time slot, which will enable multiple wireless sensor nodes to work together.

The overall power budget of the wireless system, the transmit power consumption, the receiver power consumption, the standby power consumption, and the start-up time are all important considerations and will determine how much current the unit will consume when transmitting and receiving data.

To minimise the overall power consumption, it is not enough to simply select the lowest-power mode on the microcontroller as the amount of work needed to complete each of the tasks will need to be taken into account and as the Internet of Things develops and the amount of data collated rises, how and when that data is processed will become more important. At the moment, batteries remain the dominant way in which power is stored and delivered. While there has been a lot of discussion around energy harvesting, it really hasn’t taken off.

When you develop a network, there will be a power budget for computation and for communication. Hopping from one node to another to get that data to a point where it can be processed can be described, in effect, as an energy tax that you are taking from that packet or payload. Minimising those hops could be one trade-off leading to more localised processing should those tasks be more power intensive.

In many low-power saving mode systems, the application’s battery life will often be affected by the current consumption of other components in the PCB and this needs to be considered. components in the PCB and this needs to be considered. Designers will also need to  determine which other circuits need to be powered in the low-power state of the application. Power requirements will have an impact on the roll out of the Internet of Things, but everything will depend on the application.

Cost and power among the challenges to rolling out of IoT applications, but note that, further down the road, security is another consideration. Consumers will start to worry when they begin to realise the devices they are using are less secure than they thought. When you connect to a network, there are some
expensive operations that need to be carried out and that will have an impact. Any security features will
need to be low power.

Smart Homes, Sentrollers and ZigBee   Leave a comment

The estimates of how many connected devices will constitute the Smart Home market are all over the map. This sector is going to be big and will be extremely important to the future of the electronics industry

Smart Home: let us define the Smart Home as being a network of Sentrollers  – sensors, controllers and actuators, connected to a central home control box and from there to an intelligent dashboard in the cloud that can be monitored and controlled by web connected devices like smart phones.

Currently, there are 600m connected homes in the world- connected homes have some kind of internet connection. Of these, on the average, each has about ten connected wifi devices. This includes computers, laptops, phones, games, entertainment systems etc.

As the number of connected homes grows, there will be an increasing movement to incorporate sentrollers into the home. Whereas there are about 10 WiFi devices in the home today, within
ten years, we expect to see about 100 or more sentroller devices within each home.

This will include a network of different kinds of sensors spread throughout the home- temperature, motion, position, security, humidity, etc. that will track the life activity of those in the home. This includes position sensors for measuring whether a door or window is open or closed, motion sensors that track where in the house a certain occupant may be, temperature sensors to ensure that the house is at the proper temperature, while at the same time ensuring optimal use of energy (i.e. not heating or cooling the house when nobody is home. This can also include humidity sensors adjacent to plumbing fixtures to provide alerts in case of leaks.

Intelligence can enable many of these sensors to provide dual uses, i.e. when no one is in the home and the security system is on, a motion sensors can send an alarm, if it detects someone moving around. However, when the However, when the residents are home, the motion sensors can turn on lights to illuminate a path during the night or customise temperature for the room in which the person is in. The motion sensor could even activate the appropriate music selections to follow the person as they move from room to room.

Depending on their function, these sensors can communicate among themselves and to a central home control unit, which connects all the home’s systems to the internet and allows control and monitoring of the home via cloud intelligence, smart phones, tablets or other web connected devices.

Within the homes however, the devices need to talk to each other and to the central home router/network. There are a variety of wireless technology standards that can be used to tie together these sentrollers and make sure that they can reach the home control box (i.e. the router).

We believe that there will be three open standard based networks within the home. For example, WiFi – with its wide bandwidth (and power hungry) requirements, will be used for big data applications, like video streaming, music, phones, gaming, etc. In contrast, Bluetooth will be used for short range communications between low data rate devices like wearables and medical health (heart rate monitoring, fitness band). However, for most sensor applications in the home, IEEE 802.15.4 based protocols like
ZigBee will be the most suitable.

Operating in the 2.4GHz frequency range, able to transmit through walls, floors and furniture, and cover an entire house, IEEE 802.15.4 based wireless offers an ideal convergence of robustness, bandwidth, power requirement and cost.

Designers can essentially consider ZigBee as low data rate, low power WiFi. Most consumers have grown accustomed to charging their portable WiFi devices every day or so. In contrast, no one will want to
regularly change batteries on the  hundred or so sensor devices in the Smart Home of the future.
ZigBee offers the ability for a battery powered device to run for up to ten years without having to change or recharge the battery. Because ZigBee only needs to send small data packets on an occasional basis, it
does not require the power used by WiFi which continually transmits millions of data packets.

ZigBee offers various other advantages to the device developer. As an international standard, it enables design engineers the knowledge that their device can be used anywhere in the world, unlike some other non-standard wireless solutions like Zwave and EnOcean. Also, as it is an open international networking standard, there are many different companies offering ZigBee radio chips – this enables manufacturers to multisource the radio chips, not locking them into a single provider.

The new Smart Home – the Intelligent smart home – will be composed of a network of sensors, actuators and controllers – all connected by a reliable, robust and power efficient wireless connectivity standard, provides a path to the next generation, multi trillion dollar  electronic component and smart home devices market.


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