Weekly IT Digest #4: Apple's CareKit Framework Made Available, Samsung's IoT-Platform, Artik Cloud, Introduced
May 5th, 2016
Apple has released first applications that use CareKit framework, Samsung introduced Artik Cloud IoT platform at a developers' conference, and CERN made the data from Large Hadron Collider (LHC) available to the public to download and analyze.
Apple began using the CareKit mobile framework and made the CareKit code for iOS open to the public. The company presented four applications that were built using this framework: Glow Nurture, Glow Baby, Start, and One Drop. The first two apps (Glow Nurture and Glow Baby) are designed to monitor the state the mother’s body during pregnancy and to monitor the first year of baby’s life. Start is an app that monitors the use of antidepressants and One Drop is an app for diabetics.
CareKit framework allows creating apps that can track human’s body condition and includes four basic modules:
- Care Card helps to ensure that a treatment plan and other doctor’s recommendations are followed. The module can record data automatically using Apple Watch and iPhone sensors.
- Symptom and Measurement Tracker records diseases’ symptoms and person’s well-being. The module is able to measure the temperature and to notify the user in case the temperature rises. Also, users can record how they feel, for example, the level of fatigue. The module may offer users to fill out short questionnaires or add photos while physical activity data is recorded automatically from iPhone sensors.
- Insight Dashboard module communicates the information about the symptoms and following doctor’s orders and shows the effectiveness of treatment.
- Connect is another module that records data about the user’s body condition and the changes.
Neural networks have learned how to color black-and-white photographs. Artificial Intelligence system, created by Japanese scientists, can add color to black-and-white pictures and it can happen automatically, without any human intervention. A neural network is able to recognize the image that was loaded - discern the objects shown in the photo and select colors for them. At the moment, the algorithm works correctly with the pictures that were used in the neural network’s training. In the future, creators of this technology want to achieve maximum freedom in the algorithm.
Samsung has made a number of interesting announcements at a conference for developers. First of all, the South Korean tech giant introduced Artik Cloud, the IoT platform, designed to work together with IoT-gadgets. It is already known that the Artik Cloud platform will be used by Legrand company, a well-known manufacturer of sensors and IoT-gadgets.
Using connectors and open API, Artik Cloud service will enable the data exchange with other cloud and data storage services and will allow to store and analyze data from connected devices. One user can connect up to 25 devices to Artik Cloud for free and exchange up to 150 messages daily between them. The platform will also be able to interact with popular devices such as Amazon Echo, FitBit, Gear smartwatches, Nest thermostats, Raspberry Pi gadgets and other wearable devices. External data analysis services can also connect to Artik Cloud.
One more announcement from Samsung - Otto, an IoT-robot assistant for “smart” home, which uses Artik platform. Robot got a camera, microphone, speakers, and display. It can respond to simple questions, such as weather forecast or the latest news. In addition, Otto can follow some commands like turn on “smart” lighting or air conditioning. At the moment, Otto is just a “smart” gadget prototype.
Among other novelties, Samsung introduced SBC Artik 10, designed to be a basis for an IoT-network creation. The size of the Artik’s plane is 39 x 29 x 3.5 mm and its price is still unknown. Previously, Samsung presented Artik 1 and Artik 5 planes with less functionality, designed to be used with other equipment. Artik 10, on the other hand, is a complete system that can be used to build an IoT-network.
An effective network of approximately 200 sensors, made by BLIP Systems, is used in Aarhus, second largest city in Denmark. These sensors help to get an idea regarding the traffic on the streets and made adjustments in the work of public transport. The main task of the sensors’ data processing algorithms is to optimize the public transport users’ speed, taking into account all possible traffic jams. The sensors collect passengers’ smartphones’ MAC-addresses, encrypts the data, tags it with special marks and transmits it to the BLIP Systems server where the software analyzes the information. In the result, the data includes an estimated travel time, downtime duration, and the mode of motion on each part of the way. City officials use this analysis to identify the most problematic areas and ways to resolve problems. For example, changing the order of movement at an intersection and the duration of traffic signal has reduced travel time during the busiest traffic by 31% and the capacity of one of the key intersections increased by 50%. Who knows, perhaps in the nearest future such systems will allow forgetting about the nightmare that is traffic jams.
The European Organization for Nuclear Research (CERN) made 300 terabytes of data, obtained during the Large Hadron Collider operation, available for download. Scientists offer an opportunity to analyze the data to those who wish to. Granted, this data has been collected 5 years ago, in 2011. CERN processed this data, modeled 250 trillion particle collisions, and issued a press release about it. The dataset available for download comes in two options: full and lite. Lite package can be easily analyzed using a conventional home computer and you can use the free application called CernVM. We’re left to wonder about the intentions of such actions: are they looking for a talented self-taught nuclear physicist or a data analysis specialist?
Artificial Intelligence algorithms are used to combat poachers in the United States. An application called PAWS (Protection Assistant for Wildlife Security), created at the University of South Carolina analyzes the terrain, determines the places where poachers are most likely to appear, and then generates a random patrol timetable, so the patrol can catch poachers by surprise. PAWS algorithm in conjunction with CAPTURE algorithm allows determining the probability of a poachers’ attack on animals.
