What if these changes also take place in the macro level? Then, what can businesses do to embrace this wave of innovations?
Indeed, the cities where we live have also become "smarter" than ever. According to The Wall Street Journal, more cities are now using different types of data to make people's living safer and healthier and the cities' operations more efficient.
The rise of smart cities
The city works with Waze, a navigation app from Google, to improve traffic conditions. Officials are able to respond to traffic problems, such as a double-parked truck or a fender-bender more quickly.
The Department of Innovation and Technology developed an algorithm to predict the risk of a restaurant for spreading food-borne illnesses. The algorithm uses 11 variables in prediction, including a restaurant's past record of violations, length of operations, the weather condition, nearby burglaries, etc.
The data was used to inform the Department of Public Health for restaurant health inspections. The results? Since the program's initiation in 2015, it takes seven fewer days before inspectors visit restaurants with possible critical violations; 15 percent more critical violations are also reported.
Mobile data is used to help clean up the city's 22,000 miles of streets and alleyways. The city uses video and smartphones to collect data about illegal dumping, abandoned bulky items and other trash problems. The streets are labeled with three categories: being clean, somewhat clean and not clean. This program has resulted in an 80 percent reduction in the number of streets categorized as "not clean."
The city of New Orleans put three data sets together to help prevent deaths in fires, including:
homes without smoke detectors (from Census Bureau surveys)
homes at the greatest risk for fire fatalities, such as those with elderly and young children (from Census Bureau surveys)
neighborhoods with a history of house fires
With the aid of machine-learning technique, the city analyzed the data and identified the blocks where fire deaths were most likely to occur. Then, the fire department was able to target high-risk neighborhoods when distributing smoke detectors. Since early 2015, the department has installed 18,000 smoke detectors, as compared to installing 800 detectors per year under the old program.
How effective is it? A few months after the program began, three families (11 people in total) were alerted by the recently installed smoke detectors about a fire, and the firefighters were able to quickly respond to the incident.
Let's imagine how restaurants and hotels can be run inside a smart city
Here are my thoughts:
Restaurants and hotels can share their availability with the city, allowing people to easily locate the restaurants or hotels with empty seats or rooms.
Historic data of traffic, including foot traffic, can be used to predict sales, allowing restaurants and hotels to better manage employees' work schedules.
Restaurants and hotels will be able to get extra help even in the last minute when the city suddenly observes increasing traffic, possibly through the standby part-timers in the city's database.
Restaurants using automated services, such as coffee shops with robot baristas and self-service facilities with no hosts, no servers and no tables, can be built on the street with fast foot traffic.
New lodging products can be invented, where customer service will be provided in a remote mobile service center. Travelers can reserve and check into a hotel room with their mobile device, use their mobile device as a room key to get into the hotel room, have items delivered to their room with a robot, and check out with their mobile device. These hotels only need to hire staff to clean the rooms after the guests check out, in addition to the staff members working in the mobile service center.
Restaurants and hotels that provide customer service with humans can still be found inside the city, but possibly limited to some specific areas, with slower foot traffic and/or a lower turnaround rate.
What are your thoughts?
*The original and full-length of this discussion was firstly published on MultiBriefs.com.