Tag Archives: business

Restaurant learning what food people like

A restaurant chain can collect data on what food people like by examining the plates collected from the tables – the more leftovers given the size of the dish, the less popular the food. However, looking at the plates and entering the data takes time. It would be much faster to automate the process. For example, there could be a small conveyor belt for dirty dishes brought back from the eating area. The dishes would be weighed to record the amount of leftovers before scraping and washing. To detect which food was left over, one option is that a camera above the belt photographs the leftovers and then a computer tries to identify the food. This is a complicated machine vision and machine learning problem. A simpler option is to serve different dishes on plates with different shapes, or patterns such as lines and circles that are easily distinguished by computer. Then the plate identifies the dish for the camera, similarly to colour-coded plates identifying the price at sushi-train restaurants.
Even less costly in terms of computation (and without any camera requirement) would be to put RFID tags or other remote-id technology in plates. Each dish would have to be served on a plate with a dish-specific RFID, so the returned plates can be exactly matched to the food served on them. Each plate becomes more costly, but not by much, because RFID tags are cheap.
A single restaurant could also collect data on leftovers, but a chain of restaurants would get a larger dataset faster, thus useful information sooner on which dishes to keep and which to discontinue.

App to measure road quality

The accelerometers in phones can detect vibrations, such as when the car that the phone is in drives through a pothole. The GPS in the phone can detect the location and speed of the car. An app that connects the jolt, location and speed (and detects whether the phone is in a moving car based on its past speed and location) can automatically measure the quality of the road. The resulting data can be automatically uploaded to a database to create an almost real-time map of road quality. The same detection and reporting would work for bike paths.
Perhaps such an app has already been created, but if not, then it would complement map software nicely. Drivers and cyclists are interested in the quality of the roads as well as the route, time and distance of getting to the destination. Map software already provides congestion data and takes traffic density into account when predicting arrival time at a destination. Road quality data would help drivers select routes to minimise damage to vehicles (and the resulting maintenance cost) and to sensitive cargo. This would be useful to trucking and delivery companies, and ambulances.
A less direct use of data on road quality collected by the app is in evaluating the level of local public services provided (one aspect of the quality of local government). Municipalities with the same climate, soil and traffic density with worse roads are probably less well run. For developing countries where data on governance quality and spending is difficult to get, road quality may be a useful proxy. The public services are correlated with the wealth of a region, so road quality is also a proxy for poverty.

A residential bike shop business model

There is an empty market niche for a neighbourhood mechanic who accepts a bike in the evening and returns it in the morning. The demand is concentrated almost entirely outside business hours – evening, early morning, weekend. Opening the residential neighbourhood shop at those times would target cyclists whose bike breaks down on the commute from work to home. An overnight fix means they would not miss their next morning’s ride and would not have to haul the bike to a city shop by some other transportation.

Currently the neighbourhood shops I have seen are open during regular business hours, perhaps close a little later and open also on the weekend. I have not checked, but they must be almost customerless in the daytime on weekdays. People go to work or school. I doubt there are enough stay-at-homes who bike enough to require a mechanic’s services frequently. People in the city may visit a city bike shop at lunch, but not a residential neighbourhood one. The local shops seem to be open exactly when the customers are not there.

Fixing a bike takes time, so cyclists leave it in the shop and come back later. It is important which time of the day the bike spends at the mechanic’s. Customers who use their bike a lot and thus need frequent service want the bike available and working mainly during rush hours, because many of them commute with it. A city bike shop open during business hours can accept a bike in the morning, fix it and give it back by the end of the workday. For the commuter, the bike is available both morning and evening. The shop does not need to store the bike overnight, so does not need to rent a large space, saving costs. In a suburban shop, customers could leave their bike one evening and pick it up the next evening, but they could not use their bike for one day’s commute then.

Load sharing between city and suburban bike shops is possible. Mechanics can work in several shops at different times. They can shift to accommodate peak demand, the timing of which differs by shop. The residential neighbourhood shop would get the most customers on the weekend or outside business hours. The city centre would get more on weekdays in the daytime (the cyclists whose bike breaks down on the way to work).