Prof. Michel Johnson is analyzing the second element of deep analytics - system [Figure 1.3]. A system is a complex grouping of interrelated parts i.e. machines and agents; it can be decomposed into a set of interacting sub-systems. A system may have single or multiple objectives; it is designed to achieve overall objectives in the best possible way. It is possible to analyze a system from the perspectives of system
state, complexity, model, environment, system dynamics, cause effect analysis, feedback loop, physical and information flows and policy decisions. A system may be open or closed loop. A hard system clearly defines objectives, decision making procedures and quantitative measures of performance. It is hard to define the objectives and qualitative measures of performance and make decisions for a soft system. The state of a system at a specific time is a set of relevant properties of the system. The complexity of a system can be analyzed in terms of number of interacting elements, number of linear and nonlinear dynamic relationships among the elements, number of goals or objectives and number of ways the system interacts with its environment. A model is an abstraction of real system. A model is isolated from its environment through model boundaries. A model may be static or dynamic, linear or non-linear based on functional relationship among various variables in a model.
Figure 1.3 : System analytics
A complex system can be analyzed from the perspectives of different branches of engineering and technology such as information and communication technology, electrical and electronics, mechanical, civil, chemical, metallurgical, biotechnology, genetic engineering, pharmacy and others. IT system can be analyzed in terms of computing, communication or networking, data, application and security schema and also application integration (EAI). An electrical system may have various subsystems such as power system, renewable energy, photonics, system control, power electronics, machines, measurement & instrumentation, illumination and high voltage engineering. A complex system may be associated with various domains of earth science such as space science, water, wind and solar power.
The basic objective of system analytics is to analyze complex, dynamic, non-linear and linear interactions in various types of systems and design new structures and policies to improve the behavior of a system. A system is associated with a problem oriented model; the basic building blocks of system dynamics are cause effects analysis, positive and negative feedback loops and physical and information flows. The basic functions of system analytics include defining a problem and model boundary, building model, testing and validation of a model, model analysis, evaluation of policy alternatives and recommendation of most viable R&D policy related to technological innovations.
System Analytics
Agents: System analysts, business analysts, technology management consultants;
Objects / entities: sustainable smart cities, smart villages, communities, smart world, smart universe;
Moves : Requirements engineering, system design, coding, prototype testing, erection, installation, testing, commissioning
Emerging technologies: Innovate a set of emerging technologies based on global security parameters and sustainable development goals. /* Refer to scope analytics, section 1 */
Poverty control
Social security (HR security, decent work, religious and cultural security, gender equality, child security, women’s empowerment, peace, justice, partnership, regulatory compliance, strong institutions): digital technology (E-Governance, Social networking, e-court, AI enabled legal system, case based reasoning);
Natural disaster security (climate change, flood, drought, storm, cyclone, earthquake, volcano, snowfall, rainfall, fire, bushfire, global warming, epidemic, astronomical hazards) (attack of wild animals, insects, paste); artificial disaster security (war, act of terrorism, bioterrorism) : Earth science, artificial rainfall, cloud physics, artificial immune system, real-time moving target search for astronomical hazards, music system;
Responsible consumption and production : digital technology (ERP, SCM);
Industry, innovation and infrastructure (smart cities, smart villages): civil, mechanical, electrical, electronics, metallurgy;
Life on land (environmental pollution, conservation of resources and forest, population control): environmental engineering, sensors, earth science;
Life below water (marine life, water pollution, global warming, oil leakage, nuclear explosion): environmental engineering, sensors, earth science, marine technology;
Let us explore requirements engineering of technologies for humanity for the people of our society and the planet, now and into the future. At its heart are the aforesaid sustainable development goals which are an urgent call for action by all developed and developing countries of the world through strategic alliance and global partnership. The fundamental building block of technologies for humanity is business model innovation - how is it possible to create new job opportunities against the threats of environmental pollution (e.g. air, water, soil, sound and light pollution)? Who are the customers and service consumers? Who are the service providers or the selling agents? What do the customers value? What should be the revenue and profit generation streams of an emerging technology? How to deliver value to the customers at appropriate cost? Following table 1.1 outlines a set of global security parameters and related emerging technologies for humanity. The next sessions (2-10) have shown the complexity analysis of these technologies in terms of scope, system, structure, security, strategy, staff-resources and skill-style- support.