Soils are formed by mineral debris, organic detritus, water and living organisms. The soil ecosystem takes millennia to form and is sustained by a web of interplay both within the soil and with the vegetation ecosystem it harbors. Alongside the introduction and increased use of chemical fertilizers, soil health became synonymous with the soil chemical and physical properties. The present paradigm of cumbersome soil sampling and physico-chemical laboratory analysis, is expensive, slow and narrow. To capture the integrative function of soils, or soil health, methods that capture and describe soils as ecosystems including also living organisms, water regulation and nutrient recycling, and that do so in near real time to allow operational management, are required. General developments in information technology and communication (ICT), microelectronics and Artificial Intelligence (AI), combined with more specific technological advancement in for instance light and microwave sensing technology have paved the way for a range of new, often miniaturized, sensors that have also evolved into new tools for soil characterization. But like in medicine, old school palpation is in-escapable also for screening soil health. As part of the EU funded project AI4SoilHealth (https://ai4soilhealth.eu) a range of novel in-situ methods are being tested at pilot sites across Europe, including: soil spectroscopy, soil penetrometers, Ion Selective Electrodes (ISE), macrofauna observation, environmental DNA (eDNA), enzymatic activity, soil aggregate stability and water infiltration. Standardizing these methods, and using the EU-wide Land Use and Coverage Area frame Survey (LUCAS) physico-chemical analysis schema as reference methods, AI is applied for developing a smart-phone operated rapid assessment framework for soil health metrics. Here we present an overview of new methods to use for in-situ soil monitoring, methods that mostly give an instant answer or can be analyzed in a home environment within a few hours.