Many children or even adults suffer from certain diseases that can be treated to a reasonable extent by using play therapy. Some computer games help to reduce or even eliminate the effects of certain conditions on these people. These types of special games that help treat or improve diseases are called therapeutic games, mostly pursued in cognitive science.

The Challenge:

• Designing cognitive games to identify or treat cognitive diseases
• Designing cognitive data collection methods with digital games
• Measuring the effectiveness of treatment methods provided for disorders

Specifications of the produced DRI in direct reduction process will affect the downstream process (steelmaking in EAF). Energy and refractory consumption in the EAF will increase, if iron and carbon content of the DRI are not uniform. Since real-time controlling of the process is not feasible, a computer model that predicts the chemical composition of the DRI based on the process parameters and would be able to suggest the optimum operational parameters to make the product as uniform as possible could be extremely beneficial. Due to complex physics of iron reduction and governing equations, utilizing artificial intelligence solutions such as ANN can result in more precise and usable data.

The Challenge:

Utilizing neural networks algorithms to predict the direct reduction process and suggesting the optimum operational parameters to make the metallization and carbon content of the DRI as uniform as possible.

Making slag in electric arc furnaces is an essential part of the process. A significant percentage of the melt in electric arc furnaces is slag which vary depending on the type and quality of input charge as well as the technology used. A portion of the formed slag contains FeO which causes iron loss and reduces the efficiency of the steel making process.

The Challenge:

Using machine learning algorithms to optimize the amount of FeO in electric arc furnaces slag.

One of the most important areas of application of artificial intelligence in the health systems is monitoring the condition of patients. The use of wearable sensors has a tremendous impact on health and the purpose of their development is to help patients, doctors and treatment teams. These technologies are developing and include watches, electrodes and flexible biometric devices that measure the biological factors of the human body. It is expected that artificial intelligence technology in the field of voice-based wearable sensors will help to detect the level of consciousness with the help of existing primary data collected such as the obtained signals related to the sound of breathing (respiratory sounds). This is done with the help of:

• Data acquisition hardware development in order to include designed software;
• Designing a system to connect the obtained data along with the results of automatic processing based on artificial intelligence with the person’s electronic file;
• Designing a doctor’s access application to a person’s electronic file;
  It will be possible to access the technology of making a complete sound-based wearable sensor system and developing the use of other sensors for 24-hour monitoring of a person’s health.

The Challenge:

How can artificial intelligence be used to detect the level of consciousness with the help of wearable respiratory sensors?

Telemedicine makes access to patients easier and allows doctors to expand their work environment. It is expected that Artificial intelligence technology in the field of tele-ophthalmology will help to:

• Design a system for connecting images taken from the eye along with the results of automatic processing with the patient’s electronic file and designing an application for expert access to the patient’s file;
• Using a mobile phone for tele-ophthalmology application;
• Preparation of a large database of eye images from reliable medical centers (multi-center study);
• Development of data acquisition hardware in order to include designed software;
• Access to the technology of making complete eye imaging systems with tele-ophthalmology capabilities; …

The Challenge:

How can artificial intelligence be used to develop tele-ophthalmology systems?

The early and accurate diagnosis of gastrointestinal diseases is critical. However, sometimes many lesions are beyond the physician’s view with conventional endoscopy. Endoscopic technology, like other technologies, has always been progressing, and it is expected that a new generation of endoscopes will be designed in the near future by using the latest micro-tools, data science and artificial intelligence so that doctors can have a clearer view of the disease from a physical and data point of view and more diagnostic efficiency.

The Challenge:

How can design a new endoscopy platform with the help of artificial intelligence to automatically detect the suspected frames to the presence of lesions.

Plastic recycling specially PET and converting to granules for reuse is one of the environmental challenges. In this challenge, the preparation of colorless granules from colored plastics is considered for recycling with higher added value.

The flocculant material is a polymer poly-electrolyte that is used for rapid precipitation of suspended particles in steel waste. Solutions for local production of this product or similar products for use in the wastewater treatment of the steel industry or other industries are considered in this challenge.

Storing, preserving, and transporting food and medicine in hot areas without access to the energy distribution grid is one of the challenges that is directly related to the health and living conditions. In the second stage of importance, providing comfortable environmental conditions for living in the hot climate of the region by using climatic potentials and local resources is included in this category. In general, providing sustainable cooling, especially in remote areas in hot climates, is one of the challenges of the countries in the region.

One of the most important challenges is energy supply, especially deprived and rural areas. Since access to the energy distribution grid is difficult or impossible in these regions, the approach of providing energy in the form of on-site production based on the climatic/regional potential will be the most likely solution. The main sources of energy in this approach are sun, wind, water and different forms of bioenergy. The important point for these types of energy is its cost, so that they can not only be competitive with fossil types, but can also be used in deprived areas.