Cities and the sharing economy

During my last days as a paid industry analyst on smart cities there was a flurry of interest from a few city administrations on how they should respond to the sharing economy. As often seems to be the case, here cities seem to have very little awareness of what efforts have been made by their peers in response to common issues or problems. It wasn’t too hard to find out which cities had made a big effort to develop a strategy for dealing with the impact of the sharing economy (some of which might be better characterised as to how they could respond to the incursions of powerful platform economy companies), but few of them seem to have done this.

So this guide for municipalities prepared by the Canadian city of Guelph looks to be really useful – particularly since it sets out six decisions that municipalities need to make, and provides a handy set of resources.

And while we’re on the subject, the Belgian city of Ghent has prepared a report (and a wiki) about commons-based initiatives in the city. The report is in Flemish…

Connected bikes shed new light on smart cities

Just over a year ago I wrote about See.Sense, a Northern Ireland-based start-up making and selling smart connected bicycle lights. The lights were pretty cool in themselves (the cyclists in my family tried one) but the really clever thing was the way in which the company was planning to make use of the data from sensors in the lights, recognising that it was now in the urban data business.

I’m pleased to be able to say that the company is still progressing along this track. This week it announced two new trials with smart city programmes – one in Dublin, where it’s one of four smart cycling pilots rolled out in the run-up to the city’s hosting the global cycling congress Velo City in 2019, and one in Manchester, where the data is being delivered to the CityVerve smart city hub so that it can be accessed and exploited by the wider community of developers.

Both pilots involve the cities’ cycling communities, and both offer the See.Sense ICON light at a highly subsidised price in return for users agreeing to share their sensor data.

This are still early days. Various use cases are being discussed (including one of my favourites, using the lights to gather crowdsourced data on surface quality) but none have been definitively adopted. There’s no commercial model either, so no sign of how See.Sense might move towards a business that isn’t just based on hardware sales. But it’s promising, and a coupe of visible signs that the value of the company’s approach is being recognised more widely.

MOOnitor: the internet of cows, with satellites

The application of the Internet of Things (IoT) to the world of agriculture has seen something of an upsurge in the last few years. There have been projects and companies offering to connect eels, vineyards, bees, and trees. Two years ago at Mobile World Congress in Barcelona both Deutsche Telekom and NTT Docomo showed off connected cow services, and it’s hard to forget a company called Findmysheep.


A cow wearing the MOOnitor collar

Nevertheless we have been impressed by a new offering from Israeli start-up MOOnitor. MOOnitor’s solution is a combination of: a cow collar with an accelerometer, solar panels and communications modules; localised software, running on a low power microcontroller to process and compress the data, to save on data traffic; a cloud platform for further analytics; and a presentation layer for a smartphone app and the web. Communications involve a one-directional satellite link that uses the Globalstar system and a bi-directional LoRa based RF link. Apart from a low power accelerometer, the only local sensor used for the application is a GPS receiver. There is a temperature sensor too, but that is only used to monitor the health of the equipment and plays no part in providing the application’s intelligence. LoRa is used, for collar maintenance when necessary, and the Globalstar link is used to send data to the cloud.

Much of the solution’s cleverness consists in its ability to conserve scarce resources. Rather than simply gather data and then send it to the cloud for heavy-duty processing, much of the work is done locally. Accelerometer measurements are converted, using an algorithm running on the local microcontroller, into numeric values corresponding the energy used by the cow during a short time period. The algorithm results are further categorized into cow activities: Resting, Grazing, and Walking.

The high resolution temporal data is summed on a daily basis, representing the amount of time that the cow has spent grazing, walking and resting. Once a day, shortly after midnight (local time, synced by the GPS), the collar sends a 36-byte message to the cloud platform. This message is derived from analysis of ~50MB of accelerometer data and three time-stamped GPS records, taken at set periods.

The solution conserves battery life as well as data transmission. Hardware that is not being used goes to sleep, so that it consumes little power. It can work for seven days on its battery alone, and the solar panels on the collar are sufficient to completely recharge the batteries in two hours. The collar itself is designed to last for ten years in harsh outdoors conditions. The cloud platform is able to make sense of the activity data to infer information about each cow. The individual cow’s measurements are compared to its own history and to those from other members of the herd. A sick cow will spend fewer hours grazing; peaks in walking activity indicate a cow in oestrus. A high proportion of repeated oestrus events indicates that cows have not conceived, and can therefore be an indication that of mis-performing breeding bulls. Cows’ activities can even be used to estimate pasture quality and herd energy balance.

A future upgrade to the collar’s software may enable the detection of heat stress in the cow. Neck movement during panting has a distinctive periodic nature. This distinct inertial pattern associated with panting can be detected locally after transformation to the frequency domain.

The ranchers app, and the web-based portal, allow farmers to see the key metrics for their herds, including the quality of the pasture, the location of individual cows (which can be located in real time via a local LoRa dongle), and which cows are pregnant, lactating or in oestrus. A key metric is the energy balance of the individual cows and the herd as a whole. Positive energy balance is a strong indicator of the cow’s welfare. Energy balance is key to the cow’s successful reproduction cycle from conceiving to calving and healthy calf at weaning. The most critical period is right after calving, when the newly born is lactating while the cow should get pregnant. . Attending to the cows’ needs will eventually increase the number of weaned calves.

The main screen of the rancher app

The main screen of the rancher app

MOOnitor is distinguished from its competitors by the very clear focus on a specific segment of cattle farming – the production of weaner calves for beef, on highly extensive farms where direct human monitoring of the herd is impractical. Although there are other ‘internet of cows’ solutions available, most of these are oriented towards dairy farming. Instead MOOnitor focuses on extensive cattle producers in Australia, the US and South America. It says that competitors are either from the dairy industry, which currently uses sensors in conjunction with monitoring milk quality, or from animal tracking companies, which have emphasised position reporting and crude measures of activity.
MOOnitor offers beef cows producers a straightforward business case. Herd performance is measured in terms of yield percentage – the proportion of cows that produce a weaned calf each year. An average extensive herd can deliver yields of 50-60%, but one that is better managed can reach yields of 85-90%. Better management, though, usually involves lots of hands-on human intervention, which is expensive; so an IoT data collection and analytics platform is obviously of interest, because it can help the farmer deliver more calves per year more profitably.

The worked example it provides is for a herd of 250 cattle, with one in five cows equipped with a monitoring collar. MOOnitor says that beef herds are for the most part managed as a collective, so monitoring some cows provides statistically reliable data while keeping costs down. This approach makes for a one time cost of USD180 per collar, and USD9,000 for the 50 cows. The farmer pays a monthly per collar fee of USD10, making the opex for the year USD6,000. Since each calf is worth USD850 at the point of sale, a 10% increase in yield (that is, 25 extra calves from the 250 cows) produces an extra income of USD21,250 – which compares well to the first year system costs of USD15,000.

At the moment MOOnitor, founded in August 2014, is a very small start-up, only employing its (admittedly impressive) three founders and a very few other part time employees , most of whom are rewarded with options rather than salaries, and with subcontracting relationships in place with another Israeli company for the small-scale manufacture of the collars. It has raised USD300,000 from angel investors to date, and is looking to increase this to USD1m through a first round funding exercise currently under way. It has a road map in place for further developments of its product, and it has a small-scale pilot in the north of Israel.

A research version of the collars, which provide higher resolution temporal activity and location data is used by the Department of Animal Production and Pastures at the School of Agronomy in the Universidad de la República Uruguay. Another research system will be used in the Department of Plant and Soil Sciences at the University of Kentucky.

MOOnitor aims to find a global distribution partner that already has reach into its chosen sector, and can provide the professional services and training that users of its services will require. The company is now exploring possibilities for an international distribution network as preparation for first commercial sales during 2016.

Car Sharing 2.0: Audi Unite

One of the most fascinating aspects of the connected car is the way in which it enables new business models as well as new products and services.

I’ve written elsewhere about car sharing so I won’t rehearse all the issues here. It’s provided by a wide range of companies. Some are conventional rental companies who are using connectivity to develop new service models; ZipCar, probably the best known car sharing company, is owned by Avis. Here the cars are owned by a company and rented out on a time basis. Car sharing is just a bit more flexible, and a bit less labour intensive, than a conventional renting business.

Other like RelayRides are much more of a P2P online marketplace, like Airbnb for cars, connecting individuals who don’t mind making their cars available to strangers with people who want to flexibly borrow a car for a short time. These are potentially much more disruptive, though of course they might fail, as the UK’s WhipCar did.

But some mainstream car manufacturers are already dipping a toe into the turbulent waters of providing ‘mobility as a service’ rather than selling boxes on wheels.  An intriguing new twist on car sharing has come from Audi; its Audi Unite service, launched in Sweden, offers a ‘personalised micro-sharing’ proposition whereby a group of individuals can collectively lease a vehicle from the company, and a combination of cloud platform, smartphone application and local signalling beacon can be used to measure the usage and share the costs.

Audi promises “transparent and convenient cost splitting between the members of the Audi unite group.” The group can decide if they would like to split the fixed cost of the car (e.g. leasing fee, insurance, tax, winter tires, service, cleaning) evenly or according to the individual usage behaviour, which most of the group chose as the option. This means, that whenever a group member books the car, drives with the car or parks it outside of the individually defined homezone, the time gets accounted to his/her bill. The unused time when the car is parked in the homezone and therefore available for the group is split evenly between all group members. Group members use a fuel card to fill up the car whenever needed and all costs are divided according to mileage.

The service concept is smart, yet also a bit weird. It’s tempting to characterize the idea as well suited to the age of automotive austerity, in which young people are increasingly delaying car purchase or avoiding it altogether.

But Audi is presenting Unite as a ‘premium’ service, and it is in essence a way to market new cars. A wide range of not-cheap vehicles are available in the program. In the company’s words, it is “concentrating on the specific requirements of premium customers. Many of them are finding the ‘shareconomy’ an inspiring idea – but out of a very specific motivation: They share not because they can’t afford something or simply want to get from A to B, but because they believe in and enjoy the shared experience.” It’s worth noting that ‘fair splitting’ has been identified by some commentators as one of the big trends for 2015.

Audi acknowledges that it doesn’t really know how this is going to turn out: “We are therefore working on new additional mobility products that offer greater flexibility while fulfilling the brand’s premium standards. We are currently in a test phase with these formats and are gathering feedback from our customers in a variety of markets so that we can examine the business case for us the manufacturer and for our dealers.”

In any case, it is a bold and brave move that deserves two cheers and further watching.

Voice quality on Skype over 4G

Earlier this week I needed to join a Skype call but found myself in central London. I mainly use Skype from my laptop, over WiFi and a fixed broadband connection, with a dedicated headset. But I didn’t have my laptop with me. I’d installed Skype on my Android phone, and might have used it over WiFi in a cafe – only the cafes are all a bit noisy. So I tried Skype over 4G as I walked about the back streets of Bloomsbury, trying to find places that were quiet and not too windy. I’m on an ‘unlimited’ data deal from 3, so why not?

I was surprised how good it was. The voice quality was really good at my end – not sure how I sounded at the other end. I know it’s not always good on Skype, but it was a lot better than the kind of voice quality that I get on telephony on the mobile network these days. Can’t help wondering what the point of the QoS on VoLTE is meant to be.